This document provides information and materials for conducting a performance appraisal for an enterprise data architect, including:
1. A sample performance appraisal form spanning 7 pages with sections for reviewing performance factors, strengths/accomplishments, areas for improvement, signature approval, and more.
2. Examples of performance review phrases for an enterprise data architect, addressing factors like attitude, creativity, decision-making, interpersonal skills, and problem-solving.
3. An overview of the top 12 methods for conducting a performance appraisal, such as management by objectives, critical incident, behaviorally anchored rating scales, and 360 degree/multi-rater feedback.
Consolidating MLOps at One of Europe’s Biggest AirportsDatabricks
At Schiphol airport we run a lot of mission critical machine learning models in production, ranging from models that predict passenger flow to computer vision models that analyze what is happening around the aircraft. Especially now in times of Covid it is paramount for us to be able to quickly iterate on these models by implementing new features, retraining them to match the new dynamics and above all to monitor them actively to see if they still fit the current state of affairs.
To achieve those needs we rely on MLFlow but have also integrated that with many of our other systems. So have we written Airflow operators for MLFlow to ease the retraining of our models, have we integrated MLFlow deeply with our CI pipelines and have we integrated it with our model monitoring tooling.
In this talk we will take you through the way we rely on MLFlow and how that enables us to release (sometimes) multiple versions of a model per week in a controlled fashion. With this set-up we are achieving the same benefits and speed as you have with a traditional software CI pipeline.
Meetup: Streaming Data Pipeline DevelopmentTimothy Spann
The document discusses streaming data pipelines and includes information about:
- The FLaNK stack which is comprised of Apache NiFi, Apache Kafka, Apache Flink, and Java.
- SQL Stream Builder which allows developers, analysts, and data scientists to write streaming applications using standard SQL without needing to write Java or Scala code.
- Apache Kafka as a distributed, partitioned, and replicated publish-subscribe messaging system.
- Apache Flink which is a framework for distributed stream and batch data processing.
Architect’s Open-Source Guide for a Data Mesh ArchitectureDatabricks
Data Mesh is an innovative concept addressing many data challenges from an architectural, cultural, and organizational perspective. But is the world ready to implement Data Mesh?
In this session, we will review the importance of core Data Mesh principles, what they can offer, and when it is a good idea to try a Data Mesh architecture. We will discuss common challenges with implementation of Data Mesh systems and focus on the role of open-source projects for it. Projects like Apache Spark can play a key part in standardized infrastructure platform implementation of Data Mesh. We will examine the landscape of useful data engineering open-source projects to utilize in several areas of a Data Mesh system in practice, along with an architectural example. We will touch on what work (culture, tools, mindset) needs to be done to ensure Data Mesh is more accessible for engineers in the industry.
The audience will leave with a good understanding of the benefits of Data Mesh architecture, common challenges, and the role of Apache Spark and other open-source projects for its implementation in real systems.
This session is targeted for architects, decision-makers, data-engineers, and system designers.
Power BI Desktop | Power BI Tutorial | Power BI Training | EdurekaEdureka!
This Edureka "Power BI Desktop" tutorial will help you to understand what is Power BI Desktop with examples and demo. Below are the topics covered in this tutorial:
1. Why Power BI?
2. What Power BI?
3. Who use Power BI?
4. Flow of Work
5. Power BI Trends
Scaling and Modernizing Data Platform with DatabricksDatabricks
This document summarizes Atlassian's adoption of Databricks to manage their growing data pipelines and platforms. It discusses the challenges they faced with their previous architecture around development time, collaboration, and costs. With Databricks, Atlassian was able to build scalable data pipelines using notebooks and connectors, orchestrate workflows with Airflow, and provide self-service analytics and machine learning to teams while reducing infrastructure costs and data engineering dependencies. The key benefits included reduced development time by 30%, decreased infrastructure costs by 60%, and increased adoption of Databricks and self-service across teams.
Whoops, The Numbers Are Wrong! Scaling Data Quality @ NetflixDataWorks Summit
Netflix is a famously data-driven company. Data is used to make informed decisions on everything from content acquisition to content delivery, and everything in-between. As with any data-driven company, it’s critical that data used by the business is accurate. Or, at worst, that the business has visibility into potential quality issues as soon as they arise. But even in the most mature data warehouses, data quality can be hard. How can we ensure high quality in a cloud-based, internet-scale, modern big data warehouse employing a variety of data engineering technologies?
In this talk, Michelle Ufford will share how the Data Engineering & Analytics team at Netflix is doing exactly that. We’ll kick things off with a quick overview of Netflix’s analytics environment, then dig into details of our data quality solution. We’ll cover what worked, what didn’t work so well, and what we plan to work on next. We’ll conclude with some tips and lessons learned for ensuring data quality on big data.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
The Rise Of Event Streaming – Why Apache Kafka Changes EverythingKai Wähner
Business digitalization trends like microservices, the Internet of Things or Machine Learning are driving the need to process events at a whole new scale, speed and efficiency. Traditional solutions like ETL/data integration or messaging are not build to serve these needs.
Today, the open source project Apache Kafka® is being used by thousands of companies including over 60% of the Fortune 100 to power and innovate their businesses by focusing their data strategies around event-driven architectures leveraging event streaming.We will discuss the market and technology changes that have given rise to Kafka and to Event Streaming, and we will introduce the audience to the key aspects of building an Event streaming platform with Kafka. Examples of productive use cases from the automotive, manufacturing and transportation sector will showcase the power of event streaming.
Consolidating MLOps at One of Europe’s Biggest AirportsDatabricks
At Schiphol airport we run a lot of mission critical machine learning models in production, ranging from models that predict passenger flow to computer vision models that analyze what is happening around the aircraft. Especially now in times of Covid it is paramount for us to be able to quickly iterate on these models by implementing new features, retraining them to match the new dynamics and above all to monitor them actively to see if they still fit the current state of affairs.
To achieve those needs we rely on MLFlow but have also integrated that with many of our other systems. So have we written Airflow operators for MLFlow to ease the retraining of our models, have we integrated MLFlow deeply with our CI pipelines and have we integrated it with our model monitoring tooling.
In this talk we will take you through the way we rely on MLFlow and how that enables us to release (sometimes) multiple versions of a model per week in a controlled fashion. With this set-up we are achieving the same benefits and speed as you have with a traditional software CI pipeline.
Meetup: Streaming Data Pipeline DevelopmentTimothy Spann
The document discusses streaming data pipelines and includes information about:
- The FLaNK stack which is comprised of Apache NiFi, Apache Kafka, Apache Flink, and Java.
- SQL Stream Builder which allows developers, analysts, and data scientists to write streaming applications using standard SQL without needing to write Java or Scala code.
- Apache Kafka as a distributed, partitioned, and replicated publish-subscribe messaging system.
- Apache Flink which is a framework for distributed stream and batch data processing.
Architect’s Open-Source Guide for a Data Mesh ArchitectureDatabricks
Data Mesh is an innovative concept addressing many data challenges from an architectural, cultural, and organizational perspective. But is the world ready to implement Data Mesh?
In this session, we will review the importance of core Data Mesh principles, what they can offer, and when it is a good idea to try a Data Mesh architecture. We will discuss common challenges with implementation of Data Mesh systems and focus on the role of open-source projects for it. Projects like Apache Spark can play a key part in standardized infrastructure platform implementation of Data Mesh. We will examine the landscape of useful data engineering open-source projects to utilize in several areas of a Data Mesh system in practice, along with an architectural example. We will touch on what work (culture, tools, mindset) needs to be done to ensure Data Mesh is more accessible for engineers in the industry.
The audience will leave with a good understanding of the benefits of Data Mesh architecture, common challenges, and the role of Apache Spark and other open-source projects for its implementation in real systems.
This session is targeted for architects, decision-makers, data-engineers, and system designers.
Power BI Desktop | Power BI Tutorial | Power BI Training | EdurekaEdureka!
This Edureka "Power BI Desktop" tutorial will help you to understand what is Power BI Desktop with examples and demo. Below are the topics covered in this tutorial:
1. Why Power BI?
2. What Power BI?
3. Who use Power BI?
4. Flow of Work
5. Power BI Trends
Scaling and Modernizing Data Platform with DatabricksDatabricks
This document summarizes Atlassian's adoption of Databricks to manage their growing data pipelines and platforms. It discusses the challenges they faced with their previous architecture around development time, collaboration, and costs. With Databricks, Atlassian was able to build scalable data pipelines using notebooks and connectors, orchestrate workflows with Airflow, and provide self-service analytics and machine learning to teams while reducing infrastructure costs and data engineering dependencies. The key benefits included reduced development time by 30%, decreased infrastructure costs by 60%, and increased adoption of Databricks and self-service across teams.
Whoops, The Numbers Are Wrong! Scaling Data Quality @ NetflixDataWorks Summit
Netflix is a famously data-driven company. Data is used to make informed decisions on everything from content acquisition to content delivery, and everything in-between. As with any data-driven company, it’s critical that data used by the business is accurate. Or, at worst, that the business has visibility into potential quality issues as soon as they arise. But even in the most mature data warehouses, data quality can be hard. How can we ensure high quality in a cloud-based, internet-scale, modern big data warehouse employing a variety of data engineering technologies?
In this talk, Michelle Ufford will share how the Data Engineering & Analytics team at Netflix is doing exactly that. We’ll kick things off with a quick overview of Netflix’s analytics environment, then dig into details of our data quality solution. We’ll cover what worked, what didn’t work so well, and what we plan to work on next. We’ll conclude with some tips and lessons learned for ensuring data quality on big data.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
The Rise Of Event Streaming – Why Apache Kafka Changes EverythingKai Wähner
Business digitalization trends like microservices, the Internet of Things or Machine Learning are driving the need to process events at a whole new scale, speed and efficiency. Traditional solutions like ETL/data integration or messaging are not build to serve these needs.
Today, the open source project Apache Kafka® is being used by thousands of companies including over 60% of the Fortune 100 to power and innovate their businesses by focusing their data strategies around event-driven architectures leveraging event streaming.We will discuss the market and technology changes that have given rise to Kafka and to Event Streaming, and we will introduce the audience to the key aspects of building an Event streaming platform with Kafka. Examples of productive use cases from the automotive, manufacturing and transportation sector will showcase the power of event streaming.
Apache Kafka and the Data Mesh | Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Many organizations focus on the licensing cost of Hadoop when considering migrating to a cloud platform. But other costs should be considered, as well as the biggest impact, which is the benefit of having a modern analytics platform that can handle all of your use cases. This session will cover lessons learned in assisting hundreds of companies to migrate from Hadoop to Databricks.
Squirreling Away $640 Billion: How Stripe Leverages Flink for Change Data Cap...Flink Forward
Flink Forward San Francisco 2022.
Being in the payments space, Stripe requires strict correctness and freshness guarantees. We rely on Flink as the natural solution for delivering on this in support of our Change Data Capture (CDC) infrastructure. We heavily rely on CDC as a tool for capturing data change streams from our databases without critically impacting database reliability, scalability, and maintainability. Data derived from these streams is used broadly across the business and powers many of our critical financial reporting systems totalling over $640 Billion in payment volume annually. We use many components of Flink’s flexible DataStream API to perform aggregations and abstract away the complexities of stream processing from our downstreams. In this talk, we’ll walk through our experience from the very beginning to what we have in production today. We’ll share stories around the technical details and trade-offs we encountered along the way.
by
Jeff Chao
Tinder and DynamoDB: It's a Match! Massive Data Migration, Zero Down Time - D...Amazon Web Services
Are you considering a massive data migration? Do you worry about downtime during a migration? Dr. JunYoung Kwak, Tinder’s Lead Engineering Manager, will share his insights on how Tinder successfully migrated critical user data to DynamoDB with zero downtime. Join us to learn how Tinder leverages DynamoDB performance and scalability to meet the needs of their growing global user base.
White Paper - Data Warehouse Project ManagementDavid Walker
This document discusses best practices for managing data warehouse projects. It outlines common problems such as setting unrealistic expectations and managing large technical architectures. It describes the key elements of project control like phases, milestones, and risks. It recommends tools for project management, issue tracking, version control, and collaboration. It also discusses effective project leadership, methodologies, and estimating techniques to improve chances of success.
RCG proposes a Big Data Proof of Concept (PoC) to demonstrate the business value of analyzing a client's data using Big Data technologies. The PoC involves:
1) Defining a business problem and objectives in a workshop with client.
2) The client collecting and anonymizing relevant data.
3) RCG loading the data into their Big Data lab and analyzing it using Big Data technologies.
4) RCG producing results, insights, and recommendations for applying Big Data and taking business actions.
The PoC requires no investment from the client and provides an opportunity to explore Big Data analytics without committing resources.
03. Business Information Requirements TemplateAlan D. Duncan
A template for the clear and unambiguous definition of business data and information requirements. (cf. “Business Requirements Document”, “Functional Specification” or similar from standard SDLC processes). As such, the contents will typically form the basis for population and publication of a business glossary of information terms.
This document discusses challenges with centralized data architectures and proposes a data mesh approach. It outlines 4 challenges: 1) centralized teams fail to scale sources and consumers, 2) point-to-point data sharing is difficult to decouple, 3) bridging operational and analytical systems is complex, and 4) legacy data stacks rely on outdated paradigms. The document then proposes a data mesh architecture with domain data as products and an operational data platform to address these challenges by decentralizing control and improving data sharing, discovery, and governance.
The document discusses building a modern data platform in AWS. It describes how Paddy Power Betfair migrated their data platforms from on-premise to AWS to gain an integrated data platform after their merger. They used services like Redshift, S3, EMR and automated their infrastructure to onboard more data over time and build advanced analytics capabilities. They benefited from AWS's scalability, security and continuous improvements while matching their workload to appropriate services.
This document provides an introduction and overview of Apache Spark with Python (PySpark). It discusses key Spark concepts like RDDs, DataFrames, Spark SQL, Spark Streaming, GraphX, and MLlib. It includes code examples demonstrating how to work with data using PySpark for each of these concepts.
- Delta Lake is an open source project that provides ACID transactions, schema enforcement, and time travel capabilities to data stored in data lakes such as S3 and ADLS.
- It allows building a "Lakehouse" architecture where the same data can be used for both batch and streaming analytics.
- Key features include ACID transactions, scalable metadata handling, time travel to view past data states, schema enforcement, schema evolution, and change data capture for streaming inserts, updates and deletes.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
This document provides an agenda and overview for a workshop on building a data lake on AWS. The agenda includes reviewing data lakes, modernizing data warehouses with Amazon Redshift, data processing with Amazon EMR, and event-driven processing with AWS Lambda. It discusses how data lakes extend traditional data warehousing approaches and how services like Redshift, EMR, and Lambda can be used for analytics in a data lake on AWS.
This document discusses the need for observability in data pipelines. It notes that real data pipelines often fail or take a long time to rerun without providing any insight into what went wrong. This is because of frequent code, data, dependency, and infrastructure changes. The document recommends taking a production engineering approach to observability using metrics, logging, and alerting tools. It also suggests experiment management and encapsulating reporting in notebooks. Most importantly, it stresses measuring everything through metrics at all stages of data ingestion and processing to better understand where issues occur.
The document discusses data architecture solutions for solving real-time, high-volume data problems with low latency response times. It recommends a data platform capable of capturing, ingesting, streaming, and optionally storing data for batch analytics. The solution should provide fast data ingestion, real-time analytics, fast action, and quick time to value. Multiple data sources like logs, social media, and internal systems would be ingested using Apache Flume and Kafka and analyzed with Spark/Storm streaming. The processed data would be stored in HDFS, Cassandra, S3, or Hive. Kafka, Spark, and Cassandra are identified as key technologies for real-time data pipelines, stream analytics, and high availability persistent storage.
Continuous Data Replication into Cloud Storage with Oracle GoldenGateMichael Rainey
Continuous flow. Streaming. Near real-time. These are all terms used to identify the business’s need for quick access to data. It’s a common request, even if the data must flow from on-premises to the cloud. Oracle GoldenGate is the data replication solution built for fast data. In this session, we’ll look at how GoldenGate can be configured to extract transactions from the Oracle database and load them into a cloud object store, such as Amazon S3. There are many different use cases for this type of continuous load of data into the cloud. We’ll explore these solutions and the various tools that can be used to access and analyze the data from the cloud object store, leaving attendees with ideas for implementing a full source-to-cloud data replication solution.
Presented at ITOUG Tech Days 2019
The document discusses Microsoft's approach to implementing a data mesh architecture using their Azure Data Fabric. It describes how the Fabric can provide a unified foundation for data governance, security, and compliance while also enabling business units to independently manage their own domain-specific data products and analytics using automated data services. The Fabric aims to overcome issues with centralized data architectures by empowering lines of business and reducing dependencies on central teams. It also discusses how domains, workspaces, and "shortcuts" can help virtualize and share data across business units and data platforms while maintaining appropriate access controls and governance.
The document introduces data engineering and provides an overview of the topic. It discusses (1) what data engineering is, how it has evolved with big data, and the required skills, (2) the roles of data engineers, data scientists, and data analysts in working with big data, and (3) the structure and schedule of an upcoming meetup on data engineering that will use an agile approach over monthly sprints.
Delta Lake brings reliability, performance, and security to data lakes. It provides ACID transactions, schema enforcement, and unified handling of batch and streaming data to make data lakes more reliable. Delta Lake also features lightning fast query performance through its optimized Delta Engine. It enables security and compliance at scale through access controls and versioning of data. Delta Lake further offers an open approach and avoids vendor lock-in by using open formats like Parquet that can integrate with various ecosystems.
DataEd Webinar: Unlocking Business Value Through Data Modeling and Data Archi...DATAVERSITY
This document summarizes a webinar on using data architecture and modeling for business value. The webinar discusses data management practices and principles like the Data Management Body of Knowledge. It then provides examples of how data architecture can help solve business problems in areas like implementing a software package, processing donations, and performing text mining and analytics. The goal is to demonstrate how data architecture is a useful tool for informing, clarifying and resolving organizational challenges.
Data Governance is becoming a more mature and better understood practice that reduces risk and creates value across all industries.
This presentation covers:
-Typical obstacles to sustainable Data Governance
- Re-energizing your program after a key player (or two) leave and other personnel challenges
- Staying relevant to the company as the business evolves over time
- Understanding the role of metrics and why they are critical
- Leveraging Communication and Stakeholder Management practices to maintain commitment
- Embedding Data Governance into the operations of the company
Apache Kafka and the Data Mesh | Michael Noll, ConfluentHostedbyConfluent
Data mesh is a relatively recent term that describes a set of principles that good modern data systems uphold. A kind of “microservices” for the data-centric world. While the data mesh is not technology-specific as a pattern, the building of systems that adopt and implement data mesh principles have a relatively long history under different guises.
In this talk, we share our recommendations and picks of what every developer should know about building a streaming data mesh with Kafka. We introduce the four principles of the data mesh: domain-driven decentralization, data as a product, self-service data platform, and federated governance. We then cover topics such as the differences between working with event streams versus centralized approaches and highlight the key characteristics that make streams a great fit for implementing a mesh, such as their ability to capture both real-time and historical data. We’ll examine how to onboard data from existing systems into a mesh, modelling the communication within the mesh, how to deal with changes to your domain’s “public” data, give examples of global standards for governance, and discuss the importance of taking a product-centric view on data sources and the data sets they share.
Many organizations focus on the licensing cost of Hadoop when considering migrating to a cloud platform. But other costs should be considered, as well as the biggest impact, which is the benefit of having a modern analytics platform that can handle all of your use cases. This session will cover lessons learned in assisting hundreds of companies to migrate from Hadoop to Databricks.
Squirreling Away $640 Billion: How Stripe Leverages Flink for Change Data Cap...Flink Forward
Flink Forward San Francisco 2022.
Being in the payments space, Stripe requires strict correctness and freshness guarantees. We rely on Flink as the natural solution for delivering on this in support of our Change Data Capture (CDC) infrastructure. We heavily rely on CDC as a tool for capturing data change streams from our databases without critically impacting database reliability, scalability, and maintainability. Data derived from these streams is used broadly across the business and powers many of our critical financial reporting systems totalling over $640 Billion in payment volume annually. We use many components of Flink’s flexible DataStream API to perform aggregations and abstract away the complexities of stream processing from our downstreams. In this talk, we’ll walk through our experience from the very beginning to what we have in production today. We’ll share stories around the technical details and trade-offs we encountered along the way.
by
Jeff Chao
Tinder and DynamoDB: It's a Match! Massive Data Migration, Zero Down Time - D...Amazon Web Services
Are you considering a massive data migration? Do you worry about downtime during a migration? Dr. JunYoung Kwak, Tinder’s Lead Engineering Manager, will share his insights on how Tinder successfully migrated critical user data to DynamoDB with zero downtime. Join us to learn how Tinder leverages DynamoDB performance and scalability to meet the needs of their growing global user base.
White Paper - Data Warehouse Project ManagementDavid Walker
This document discusses best practices for managing data warehouse projects. It outlines common problems such as setting unrealistic expectations and managing large technical architectures. It describes the key elements of project control like phases, milestones, and risks. It recommends tools for project management, issue tracking, version control, and collaboration. It also discusses effective project leadership, methodologies, and estimating techniques to improve chances of success.
RCG proposes a Big Data Proof of Concept (PoC) to demonstrate the business value of analyzing a client's data using Big Data technologies. The PoC involves:
1) Defining a business problem and objectives in a workshop with client.
2) The client collecting and anonymizing relevant data.
3) RCG loading the data into their Big Data lab and analyzing it using Big Data technologies.
4) RCG producing results, insights, and recommendations for applying Big Data and taking business actions.
The PoC requires no investment from the client and provides an opportunity to explore Big Data analytics without committing resources.
03. Business Information Requirements TemplateAlan D. Duncan
A template for the clear and unambiguous definition of business data and information requirements. (cf. “Business Requirements Document”, “Functional Specification” or similar from standard SDLC processes). As such, the contents will typically form the basis for population and publication of a business glossary of information terms.
This document discusses challenges with centralized data architectures and proposes a data mesh approach. It outlines 4 challenges: 1) centralized teams fail to scale sources and consumers, 2) point-to-point data sharing is difficult to decouple, 3) bridging operational and analytical systems is complex, and 4) legacy data stacks rely on outdated paradigms. The document then proposes a data mesh architecture with domain data as products and an operational data platform to address these challenges by decentralizing control and improving data sharing, discovery, and governance.
The document discusses building a modern data platform in AWS. It describes how Paddy Power Betfair migrated their data platforms from on-premise to AWS to gain an integrated data platform after their merger. They used services like Redshift, S3, EMR and automated their infrastructure to onboard more data over time and build advanced analytics capabilities. They benefited from AWS's scalability, security and continuous improvements while matching their workload to appropriate services.
This document provides an introduction and overview of Apache Spark with Python (PySpark). It discusses key Spark concepts like RDDs, DataFrames, Spark SQL, Spark Streaming, GraphX, and MLlib. It includes code examples demonstrating how to work with data using PySpark for each of these concepts.
- Delta Lake is an open source project that provides ACID transactions, schema enforcement, and time travel capabilities to data stored in data lakes such as S3 and ADLS.
- It allows building a "Lakehouse" architecture where the same data can be used for both batch and streaming analytics.
- Key features include ACID transactions, scalable metadata handling, time travel to view past data states, schema enforcement, schema evolution, and change data capture for streaming inserts, updates and deletes.
Presentation on Data Mesh: The paradigm shift is a new type of eco-system architecture, which is a shift left towards a modern distributed architecture in which it allows domain-specific data and views “data-as-a-product,” enabling each domain to handle its own data pipelines.
This document provides an agenda and overview for a workshop on building a data lake on AWS. The agenda includes reviewing data lakes, modernizing data warehouses with Amazon Redshift, data processing with Amazon EMR, and event-driven processing with AWS Lambda. It discusses how data lakes extend traditional data warehousing approaches and how services like Redshift, EMR, and Lambda can be used for analytics in a data lake on AWS.
This document discusses the need for observability in data pipelines. It notes that real data pipelines often fail or take a long time to rerun without providing any insight into what went wrong. This is because of frequent code, data, dependency, and infrastructure changes. The document recommends taking a production engineering approach to observability using metrics, logging, and alerting tools. It also suggests experiment management and encapsulating reporting in notebooks. Most importantly, it stresses measuring everything through metrics at all stages of data ingestion and processing to better understand where issues occur.
The document discusses data architecture solutions for solving real-time, high-volume data problems with low latency response times. It recommends a data platform capable of capturing, ingesting, streaming, and optionally storing data for batch analytics. The solution should provide fast data ingestion, real-time analytics, fast action, and quick time to value. Multiple data sources like logs, social media, and internal systems would be ingested using Apache Flume and Kafka and analyzed with Spark/Storm streaming. The processed data would be stored in HDFS, Cassandra, S3, or Hive. Kafka, Spark, and Cassandra are identified as key technologies for real-time data pipelines, stream analytics, and high availability persistent storage.
Continuous Data Replication into Cloud Storage with Oracle GoldenGateMichael Rainey
Continuous flow. Streaming. Near real-time. These are all terms used to identify the business’s need for quick access to data. It’s a common request, even if the data must flow from on-premises to the cloud. Oracle GoldenGate is the data replication solution built for fast data. In this session, we’ll look at how GoldenGate can be configured to extract transactions from the Oracle database and load them into a cloud object store, such as Amazon S3. There are many different use cases for this type of continuous load of data into the cloud. We’ll explore these solutions and the various tools that can be used to access and analyze the data from the cloud object store, leaving attendees with ideas for implementing a full source-to-cloud data replication solution.
Presented at ITOUG Tech Days 2019
The document discusses Microsoft's approach to implementing a data mesh architecture using their Azure Data Fabric. It describes how the Fabric can provide a unified foundation for data governance, security, and compliance while also enabling business units to independently manage their own domain-specific data products and analytics using automated data services. The Fabric aims to overcome issues with centralized data architectures by empowering lines of business and reducing dependencies on central teams. It also discusses how domains, workspaces, and "shortcuts" can help virtualize and share data across business units and data platforms while maintaining appropriate access controls and governance.
The document introduces data engineering and provides an overview of the topic. It discusses (1) what data engineering is, how it has evolved with big data, and the required skills, (2) the roles of data engineers, data scientists, and data analysts in working with big data, and (3) the structure and schedule of an upcoming meetup on data engineering that will use an agile approach over monthly sprints.
Delta Lake brings reliability, performance, and security to data lakes. It provides ACID transactions, schema enforcement, and unified handling of batch and streaming data to make data lakes more reliable. Delta Lake also features lightning fast query performance through its optimized Delta Engine. It enables security and compliance at scale through access controls and versioning of data. Delta Lake further offers an open approach and avoids vendor lock-in by using open formats like Parquet that can integrate with various ecosystems.
DataEd Webinar: Unlocking Business Value Through Data Modeling and Data Archi...DATAVERSITY
This document summarizes a webinar on using data architecture and modeling for business value. The webinar discusses data management practices and principles like the Data Management Body of Knowledge. It then provides examples of how data architecture can help solve business problems in areas like implementing a software package, processing donations, and performing text mining and analytics. The goal is to demonstrate how data architecture is a useful tool for informing, clarifying and resolving organizational challenges.
Data Governance is becoming a more mature and better understood practice that reduces risk and creates value across all industries.
This presentation covers:
-Typical obstacles to sustainable Data Governance
- Re-energizing your program after a key player (or two) leave and other personnel challenges
- Staying relevant to the company as the business evolves over time
- Understanding the role of metrics and why they are critical
- Leveraging Communication and Stakeholder Management practices to maintain commitment
- Embedding Data Governance into the operations of the company
Enterprise Data World Webinars: Master Data Management: Ensuring Value is Del...DATAVERSITY
Now that your organization has decided to move forward with Master Data Management (MDM), how do you make sure that you get the most value from your investment? In this webinar, we will cover the critical success factors of MDM that ensure your master data is used across the enterprise to drive business value. We cover:
· The key processes involved in mastering data
· Data Governance’s role in mastering data
· Leveraging data stewards to make your MDM program efficient
· How to extend MDM from one domain to multiple domains
· Ensuring MDM aligns to business goals and priorities
Presented at eMetrics Boston 2012. Defines the organizational challenges and key performance indicators for those considering the applications of Big Data in their organization.
User experience architect performance appraisallopedhapper
This document provides information and materials for evaluating the performance of a user experience architect, including:
1. A sample performance evaluation form with ratings, factors, and sections for comments.
2. Examples of performance review phrases for various factors like attitude, creativity, decision-making, and teamwork.
3. An overview of the top 12 methods for performance appraisal, such as management by objectives, critical incident, behaviorally anchored rating scales, and 360 degree feedback.
Designed to address more mature programs, this tutorial covers the issues and approaches to sustaining Data Governance and value creation over time, amongst a changing business and personnel environment.
Part of the reason many companies launch a Data Governance program again and again is that over time, it is challenging to maintain the enthusiasm and excitement that accompanies a newly initiated program.
Learn about:
• Typical obstacles to sustainable Data Governance
• Re-energizing your program after a key player (or two) leave and other personnel challenges
• Staying relevant to the company as the business evolves over time
• Understanding the role of metrics and why they are critical
• Leveraging Communication and Stakeholder Management practices to maintain commitment
• Embedding Data Governance into the operations of the company
Setting Some Realistic Enterprise Architecture GoalsPaul Ramsay
The document is a presentation on enterprise architecture given by Paul Ramsay. It discusses key topics such as the benefits of enterprise architecture, challenges of unintegrated systems, selecting an architecture framework, demonstrating results and value, and ensuring long-term viability of the architecture. The presentation provides an overview of enterprise architecture concepts and considerations for organizations.
This document provides information and resources for evaluating the performance of an ETL architect, including:
1. Sample performance evaluation forms for an ETL architect with rating scales and categories like administration, knowledge, communication, etc.
2. Examples of positive and negative phrases to use in a performance review for an ETL architect for areas like attitude, creativity, decision making, interpersonal skills, and problem solving.
3. An overview of the top 12 methods for performing a performance appraisal for an ETL architect, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360 degree feedback.
The path to a Modern Data Architecture in Financial ServicesHortonworks
Delivering Data-Driven Applications at the Speed of Business: Global Banking AML use case.
Chief Data Officers in financial services have unique challenges: they need to establish an effective data ecosystem under strict governance and regulatory requirements. They need to build the data-driven applications that enable risk and compliance initiatives to run efficiently. In this webinar, we will discuss the case of a global banking leader and the anti-money laundering solution they built on the data lake. With a single platform to aggregate structured and unstructured information essential to determine and document AML case disposition, they reduced mean time for case resolution by 75%. They have a roadmap for building over 150 data-driven applications on the same search-based data discovery platform so they can mitigate risks and seize opportunities, at the speed of business.
The document provides information about what a data warehouse is and why it is important. A data warehouse is a relational database designed for querying and analysis that contains historical data from transaction systems and other sources. It allows organizations to access, analyze, and report on integrated information to support business processes and decisions.
This document discusses key performance indicators (KPIs) for technical architects. It provides steps to create KPIs for technical architects, including defining objectives, identifying key result areas and tasks, and determining methods to measure results. The document also discusses mistakes to avoid, such as creating too many KPIs or ones that do not change based on goals. Finally, it recommends visiting an external website for additional KPI materials tailored for technical architects.
Business process architect performance appraisalmorganabbie765
Business process architect job description,Business process architect goals & objectives,Business process architect KPIs & KRAs,Business process architect self appraisal
Business systems specialist performance appraisalcameronwood054
Business systems specialist job description,Business systems specialist goals & objectives,Business systems specialist KPIs & KRAs,Business systems specialist self appraisal
This document provides information and materials for evaluating the performance of a senior structural engineer, including:
1. A sample performance evaluation form with rating scales for evaluating an engineer on factors like administration, knowledge, communication, and more.
2. Examples of performance review phrases for evaluating an engineer's attitude, creativity, decision-making, interpersonal skills, and problem-solving.
3. An overview of the top 12 methods for performance appraisal, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360 degree feedback.
This document provides information on performance appraisal methods for commercial engineers. It discusses 12 different methods: 1) Management by Objectives, 2) Critical Incident Method, 3) Behaviorally Anchored Rating Scales, 4) Behavioral Observation Scales, 5) 360 Degree Performance Appraisal, 6) Checklist and Weighted Checklist Method, 7) Graphic Rating Scale, 8) Forced Distribution Method, 9) Field Review Method, 10) Essay or Narrative Evaluation, 11) Comparative Ranking, and 12) Paired Comparison Method. For each method, it provides a brief overview and highlights some key advantages and disadvantages. The document aims to inform commercial engineers and their managers about different approaches that
Information systems engineer job description,Information systems engineer goals & objectives,Information systems engineer KPIs & KRAs,Information systems engineer self appraisal
Data centre operator performance appraisalguucinadal
This document provides information and resources for evaluating the performance of a data centre operator. It includes sample performance review forms, phrases for writing performance reviews, and descriptions of common performance appraisal methods. The top part of the document outlines a sample two-page performance review form for a data centre operator, including sections to rate job performance factors, document employee strengths and areas for improvement, and obtain signatures. The second part provides example positive and negative phrases to use when writing reviews for various performance dimensions such as attitude, decision-making, and teamwork. The third part describes 12 common performance appraisal methods, such as management by objectives, critical incident technique, behaviorally anchored rating scales, and 360-degree feedback.
This document provides information and resources for evaluating the performance of a storage architect. It includes:
1. A sample job performance evaluation form with sections for reviewing performance factors, employee strengths/accomplishments, areas for improvement, and signatures.
2. Examples of performance review phrases for evaluating a storage architect's attitude, creativity, decision-making, interpersonal skills, and problem-solving abilities.
3. An overview of the top 12 methods for conducting a storage architect's performance appraisal, including Management by Objectives, Critical Incident Method, Behaviorally Anchored Rating Scales, and 360 Degree Feedback.
This document provides information and resources for evaluating the performance of a SOA architect. It includes:
1. Links to free ebooks and forms for performance appraisals.
2. Examples of a job performance evaluation form that can be used to rate an SOA architect's performance, including factors like administration, knowledge, communication, and customer responsiveness.
3. Phrases that can be used in performance reviews to describe an SOA architect's strengths, areas for improvement, and overall performance.
4. An overview of the top 12 methods that can be used to evaluate an SOA architect's performance, such as management by objectives, critical incident method, and 360 degree feedback.
Server support engineer performance appraisallopedhapper
This document provides information and resources for evaluating the performance of a server support engineer, including:
1. A sample performance evaluation form with rating scales and categories to evaluate an employee's skills, strengths, areas for improvement, and overall performance.
2. Examples of phrases to use in a performance review for various categories like attitude, problem solving, teamwork, and decision making.
3. An overview of the top 12 methods for conducting a performance appraisal, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360 degree feedback.
This document provides information and resources for conducting a performance appraisal for a senior civil engineer. It includes:
1. A sample performance appraisal form with sections for reviewing job performance based on key criteria, identifying strengths and areas for improvement, setting goals, and obtaining signatures.
2. Examples of performance review phrases focused on attributes like attitude, creativity, decision-making, interpersonal skills, and problem-solving.
3. An overview of the top 12 methods for conducting performance appraisals, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360-degree feedback.
This document provides information and resources for evaluating the performance of a quality assurance (QA) architect, including:
1. Sample performance evaluation forms for a QA architect with ratings, factors, and sections for comments.
2. Examples of phrases to use in a QA architect's performance review for areas like attitude, creativity, decision-making, interpersonal skills, and problem-solving.
3. An overview of the top 12 methods for performing a QA architect's performance appraisal, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360-degree feedback.
Process architect performance appraisallopedhapper
This document provides information and resources for evaluating the performance of a process architect. It includes:
1. A job performance evaluation form with sections for reviewing performance factors, strengths/accomplishments, areas for improvement, signature approval, and a job description review.
2. Examples of performance review phrases for evaluating a process architect's attitude, creativity, decision-making, interpersonal skills, and problem-solving abilities.
3. An overview of the top 12 methods for conducting a process architect's performance appraisal, including Management by Objectives, Critical Incident Method, Behaviorally Anchored Rating Scales, and 360 Degree Feedback.
This document provides information and resources for conducting a performance appraisal for a naval architect. It includes a sample job performance evaluation form with sections for reviewing performance factors, employee strengths and accomplishments, areas for improvement, and a performance review plan. It also gives examples of performance review phrases for evaluating different skills and behaviors. Finally, it outlines the top 12 methods for conducting performance appraisals, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360 degree feedback. The overall document serves as a guide for naval architects to structure performance evaluations and assessments.
It field engineer performance appraisallopedhapper
This document contains materials for evaluating the performance of an IT field engineer, including:
1. A sample performance evaluation form with ratings categories and evaluation criteria covering areas like administration, communication, teamwork, and customer service.
2. Examples of performance review phrases focused on attributes like attitude, creativity, and decision-making that could be used in a performance review.
3. The document provides guidance on completing a performance review, setting performance goals, and developing improvement plans for an IT field engineer.
This document provides information and resources for conducting an interior architect's performance appraisal, including:
1. A sample performance evaluation form with sections for reviewing performance factors, strengths/accomplishments, areas for improvement, and signatures.
2. Examples of performance review phrases for evaluating an interior architect's attitude, creativity, decision-making, interpersonal skills, and problem-solving abilities.
3. An overview of the top 12 methods for conducting a performance appraisal, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360-degree feedback.
This document contains materials for evaluating the performance of a fabrication engineer, including:
1) A multi-page performance evaluation form with ratings scales to assess an engineer's skills, behaviors, and overall performance.
2) Examples of performance review phrases focused on attitude, creativity, innovation, and decision-making.
3) Links to additional online resources for performance appraisals, including sample forms, methods, tips for self-appraisals, and common key performance indicators (KPIs).
The evaluation form and review phrases are intended to provide structured guidance for assessing a fabrication engineer's job performance and developing improvement plans.
This document provides information and examples for evaluating the performance of a corrosion engineer. It includes:
1. A sample performance evaluation form for a corrosion engineer with ratings in various performance areas like knowledge, communication, decision making, and customer service.
2. Examples of performance review phrases for a corrosion engineer focused on areas such as attitude, creativity, decision making, interpersonal skills, and problem solving.
3. An overview of the top 12 methods for corrosion engineer performance appraisal, including Management by Objectives, Critical Incident Method, Behaviorally Anchored Rating Scales, and 360 Degree Feedback.
This document provides information and resources for evaluating the performance of an applications architect, including:
1. A 6-page performance evaluation form for rating an applications architect on various performance factors and collecting feedback.
2. Sample phrases for writing performance reviews on topics like attitude, creativity, decision-making, interpersonal skills, and problem-solving.
3. An overview of the top 12 methods for performing performance appraisals, such as management by objectives, critical incident method, behaviorally anchored rating scales, and 360-degree feedback.
Industrial Tech SW: Category Renewal and CreationChristian Dahlen
Every industrial revolution has created a new set of categories and a new set of players.
Multiple new technologies have emerged, but Samsara and C3.ai are only two companies which have gone public so far.
Manufacturing startups constitute the largest pipeline share of unicorns and IPO candidates in the SF Bay Area, and software startups dominate in Germany.
Best practices for project execution and deliveryCLIVE MINCHIN
A select set of project management best practices to keep your project on-track, on-cost and aligned to scope. Many firms have don't have the necessary skills, diligence, methods and oversight of their projects; this leads to slippage, higher costs and longer timeframes. Often firms have a history of projects that simply failed to move the needle. These best practices will help your firm avoid these pitfalls but they require fortitude to apply.
B2B payments are rapidly changing. Find out the 5 key questions you need to be asking yourself to be sure you are mastering B2B payments today. Learn more at www.BlueSnap.com.
Storytelling is an incredibly valuable tool to share data and information. To get the most impact from stories there are a number of key ingredients. These are based on science and human nature. Using these elements in a story you can deliver information impactfully, ensure action and drive change.
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Navigating the world of forex trading can be challenging, especially for beginners. To help you make an informed decision, we have comprehensively compared the best forex brokers in India for 2024. This article, reviewed by Top Forex Brokers Review, will cover featured award winners, the best forex brokers, featured offers, the best copy trading platforms, the best forex brokers for beginners, the best MetaTrader brokers, and recently updated reviews. We will focus on FP Markets, Black Bull, EightCap, IC Markets, and Octa.
Brian Fitzsimmons on the Business Strategy and Content Flywheel of Barstool S...Neil Horowitz
On episode 272 of the Digital and Social Media Sports Podcast, Neil chatted with Brian Fitzsimmons, Director of Licensing and Business Development for Barstool Sports.
What follows is a collection of snippets from the podcast. To hear the full interview and more, check out the podcast on all podcast platforms and at www.dsmsports.net
How to Implement a Real Estate CRM SoftwareSalesTown
To implement a CRM for real estate, set clear goals, choose a CRM with key real estate features, and customize it to your needs. Migrate your data, train your team, and use automation to save time. Monitor performance, ensure data security, and use the CRM to enhance marketing. Regularly check its effectiveness to improve your business.
How are Lilac French Bulldogs Beauty Charming the World and Capturing Hearts....Lacey Max
“After being the most listed dog breed in the United States for 31
years in a row, the Labrador Retriever has dropped to second place
in the American Kennel Club's annual survey of the country's most
popular canines. The French Bulldog is the new top dog in the
United States as of 2022. The stylish puppy has ascended the
rankings in rapid time despite having health concerns and limited
color choices.”
Structural Design Process: Step-by-Step Guide for BuildingsChandresh Chudasama
The structural design process is explained: Follow our step-by-step guide to understand building design intricacies and ensure structural integrity. Learn how to build wonderful buildings with the help of our detailed information. Learn how to create structures with durability and reliability and also gain insights on ways of managing structures.
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Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
The Genesis of BriansClub.cm Famous Dark WEb PlatformSabaaSudozai
BriansClub.cm, a famous platform on the dark web, has become one of the most infamous carding marketplaces, specializing in the sale of stolen credit card data.
[To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations]
This PowerPoint compilation offers a comprehensive overview of 20 leading innovation management frameworks and methodologies, selected for their broad applicability across various industries and organizational contexts. These frameworks are valuable resources for a wide range of users, including business professionals, educators, and consultants.
Each framework is presented with visually engaging diagrams and templates, ensuring the content is both informative and appealing. While this compilation is thorough, please note that the slides are intended as supplementary resources and may not be sufficient for standalone instructional purposes.
This compilation is ideal for anyone looking to enhance their understanding of innovation management and drive meaningful change within their organization. Whether you aim to improve product development processes, enhance customer experiences, or drive digital transformation, these frameworks offer valuable insights and tools to help you achieve your goals.
INCLUDED FRAMEWORKS/MODELS:
1. Stanford’s Design Thinking
2. IDEO’s Human-Centered Design
3. Strategyzer’s Business Model Innovation
4. Lean Startup Methodology
5. Agile Innovation Framework
6. Doblin’s Ten Types of Innovation
7. McKinsey’s Three Horizons of Growth
8. Customer Journey Map
9. Christensen’s Disruptive Innovation Theory
10. Blue Ocean Strategy
11. Strategyn’s Jobs-To-Be-Done (JTBD) Framework with Job Map
12. Design Sprint Framework
13. The Double Diamond
14. Lean Six Sigma DMAIC
15. TRIZ Problem-Solving Framework
16. Edward de Bono’s Six Thinking Hats
17. Stage-Gate Model
18. Toyota’s Six Steps of Kaizen
19. Microsoft’s Digital Transformation Framework
20. Design for Six Sigma (DFSS)
To download this presentation, visit:
https://www.oeconsulting.com.sg/training-presentations
Part 2 Deep Dive: Navigating the 2024 Slowdownjeffkluth1
Introduction
The global retail industry has weathered numerous storms, with the financial crisis of 2008 serving as a poignant reminder of the sector's resilience and adaptability. However, as we navigate the complex landscape of 2024, retailers face a unique set of challenges that demand innovative strategies and a fundamental shift in mindset. This white paper contrasts the impact of the 2008 recession on the retail sector with the current headwinds retailers are grappling with, while offering a comprehensive roadmap for success in this new paradigm.
2. Useful performance appraisal materials for enterprise data
architect:
• performanceappraisal360.com/free-ebook-2456-phrases-for-performance-
appraisals
• performanceappraisal360.com/free-65-performance-appraisal-forms
• performanceappraisal360.com/free-ebook-top-12-methods-for-performance-
appraisal
• performanceappraisal360.com/free-ebook-top-15-secrets-to-set-up-
performance-management-system
• performanceappraisal360.com/free-ebook-2436-KPI-samples/
• performanceappraisal360.com/free-ebook-top -9-tips-to-writing-a-winning-
self-appraisal
• Enterprise data architect job description
• Enterprise data architect goals & objectives
• Enterprise data architect KPIs & KRAs
• Enterprise data architect self appraisal
Job Performance Evaluation Form
Page 2
3. I. Enterprise data architect performance form
Name:
Evaluation Period:
Title: Date:
PERFORMANCE PLANNING AND RESULTS
Performance Review
• Use a current job description (job descriptions are available on the HR web page).
• Rate the person's level of performance, using the definitions below.
• Review with employee each performance factor used to evaluate his/her work performance.
• Give an overall rating in the space provided, using the definitions below as a guide.
Performance Rating Definitions
The following ratings must be used to ensure commonality of language and consistency on
overall ratings: (There should be supporting comments to justify ratings of “Outstanding” “Below Expectations,
and “Unsatisfactory”)
Outstanding Performance is consistently superior
Exceeds Expectations Performance is routinely above job requirements
Meets Expectations Performance is regularly competent and dependable
Below Expectations Performance fails to meet job requirements on a frequent basis
Unsatisfactory Performance is consistently unacceptable
A. PERFORMANCE FACTORS (use job description as basis of this evaluation).
Job Performance Evaluation Form
Page 3
4. Administration - Measures effectiveness in planning,
organizing and efficiently handling activities and eliminating
unnecessary activities
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Knowledge of Work - Consider employee's skill level,
knowledge and understanding of all phases of the job and
those requiring improved skills and/or experience.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Communication - Measures effectiveness in listening to
others, expressing ideas, both orally and in writing and
providing relevant and timely information to management,
co-workers, subordinates and customers.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Teamwork - Measures how well this individual gets along
with fellow employees, respects the rights of other
employees and shows a cooperative spirit.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Decision Making/Problem Solving - Measures
effectiveness in understanding problems and making timely,
practical decisions.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Expense Management - Measures effectiveness in
establishing appropriate reporting and control procedures;
operating efficiently at lowest cost; staying within
established budgets.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Human Resource Management - Measures effectiveness in
selecting qualified people; evaluating subordinates'
performance; strengths and development needs; providing
constructive feedback, and taking appropriate and timely
action with marginal or unsatisfactory performers. Also
considers efforts to further the university goal of equal
employment opportunity.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Independent Action - Measures effectiveness in time
management; initiative and independent action within
prescribed limits.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Job Performance Evaluation Form
Page 4
5. Job Knowledge - Measures effectiveness in keeping
knowledgeable of methods, techniques and skills required
in own job and related functions; remaining current on new
developments affecting SPSU and its work activities.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Leadership - Measures effectiveness in accomplishing
work assignments through subordinates; establishing
challenging goals; delegating and coordinating effectively;
promoting innovation and team effort.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Managing Change and Improvement - Measures
effectiveness in initiating changes, adapting to necessary
changes from old methods when they are no longer
practical, identifying new methods and generating
improvement in facility's performance.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Customer Responsiveness - Measures responsiveness and
courtesy in dealing with internal staff, external customers
and vendors; employee projects a courteous manner.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Personal Appearance - Measures neatness and personal
hygiene appropriate to position.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Dependability - Measures how well employee complies
with instructions and performs under unusual
circumstances; consider record of attendance and
punctuality.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Safety - Measures individual's work habits and attitudes as
they apply to working safely. Consider their contribution to
accident prevention, safety awareness, ability to care for
SPSU property and keep workspace safe and tidy.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Employee's Responsiveness - Measures responsiveness in
completing job tasks in a timely manner.
Outstanding
Exceeds Expectations
Meets Expectations
Below Expectations
Unsatisfactory
NA
Job Performance Evaluation Form
Page 5
6. B. EMPLOYEE STRENGTHS AND ACCOMPLISHMENTS: Include those which are relevant
during this evaluation period. This should be related to performance or behavioral
aspects you appreciated in their performance.
C. PERFORMANCE AREAS WHICH NEED IMPROVEMENT:
D. PLAN OF ACTION TOWARD IMPROVED PERFORMANCE:
Job Performance Evaluation Form
Page 6
7. E. EMPLOYEE COMMENTS:
F. JOB DESCRIPTION REVIEW SECTION: (Please check the appropriate box.)
Employee job description has been reviewed during this evaluation and no changes
have been made to the job description at this time.
Employee job description has been reviewed during this evaluation and modifications
have been proposed to the job description. The modified job description is attached to
this evaluation.
G. SIGNATURES:
Employee Date
(Signature does not necessarily denote agreement with official review and means only that the employee was
given the opportunity to discuss the official review with the supervisor.)
Evaluated by Date
Reviewed by Date
Job Performance Evaluation Form
Page 7
8. II. Enterprise data architect performance phrases
1.Attitude Performance Review Examples – enterprise data architect
Positive review
• Holly has one of those attitudes that is always positive. She frequently has a smile on her
face and you can tell she enjoys her job.
• Greg is a cheerful guy who always makes you feel delighted when you’re around him.
We are fortunate to have Greg on our team.
• Thom has an even demeanor through good times and bad. His constant cheer helps others
keep their “enthusiasm” – both positive and negative – in check.
Negative review
• Jim frequently gives off “an air” of superiority to his coworkers. He is not approachable
and is rough to work with.
• Bill has a dreadful outlook at times which has a tendency to bring down the entire team.
• For the most part, Lenny is a personable guy, but when he gets upset, his attitude turns
shocking. Lenny needs to balance his personality out and not react so much to negative
events.
2.Creativity and Innovation Performance Review Phrases for enterprise data architect
Positive review
• Sally has a creative touch in a sometimes monotonous role within our team – the way she
adds inspiration to the day to day tasks she performs is admirable.
• When a major problem arises, we frequently turn to Jon for his creativity in solving
problems. The way he can look at an issue from different sides is a great resource to our
team.
Job Performance Evaluation Form
Page 8
9. • Whenever we need a fresh look at a problem, we know we can turn to Julia for a novel
perspective.
Negative review
• Paul’s team feels discouraged as he often “shoots down” creative ideas without any
explanation. Paul should be more willing to listen to ideas before he rejects them outright.
• Jean does not tap into the creative side of her team and consistently overlooks the
innovate employees reporting to her.
• Kevin has a difficult time thinking “outside of the box” and creating new and untested
solutions.
3.Performance review phrases for decision making – enterprise data architect
Positive performance review phrases for decision making
A person with good decision-making skills should be a person:
• Be able to make sound fact-based judgments;
• Be able to work out multiple alternative solutions and determined the most suitable one;
• Be objective in considering a fact or situation;
• Be firm to not let the individual emotion and feeling affect on the made decision;
Negative performance review phrases for decision making
• Be hesitant in making decision and too much cautious in making the final decision which often
results in wrong decision;
• Apply complex and impractical approaches in solving problems;
• Fail to make a short-list of solutions recommended by direct units;
• Be paralyzed and confused when facing tight deadlines to make decisions;
4.Interpersonal Skills Performance Review Phrases – enterprise data architect
Positive review
Job Performance Evaluation Form
Page 9
10. • Ben has a natural rapport with people and does very well at communicating with others.
• Sally has a knack for making people feel important when she speaks with them. This
translates into great opportunities for teamwork and connections to form.
• Jack makes people feel at home with him. His natural ability to work with people is a
great asset to our team.
Negative review
• Tim does not understand how crucial good working relationships with fellow team
members are.
• John has an excellent impression among the management team, yet his fellow team
members cannot stand working with him.
• Paula seems to shrink when she’s around others and does not cultivate good relations
with her co-workers.
5.Problem Solving Skills Employee Evaluation Examples – enterprise data architect
Positive review
• Greg’s investigative skills has provided a key resource for a team focused on solving
glitches. His ability to quickly assess a problem and identify potential solutions is key to
his excellent performance.
• Frank examines a problem and quickly identifies potential solutions – and then makes a
recommendation as to what solution to pursue.
• Rachel understands the testing process and how to discover a solution to a particular
problem.
Negative review
• Joan is poor at communicating problem status before it becomes a crisis.
• Bill can offer up potential solutions to a problem, but struggles to identify the best
solution.
• Unraveling a problem to discuss the core issues is a skill Janet lacks.
• Peter resists further training in problem solving, believing he is proficient, yet lacking in
many areas.
• In his technical role, we turn to James often to solve problems. He seems slow and
indecisive when presented with a major issue.
Job Performance Evaluation Form
Page 10
11. 6.Teamwork Skills Performance Appraisal Phrases – enterprise data architect
Positive review
• Harry manages his relationships with his coworkers, managers, and employees in a
professional manner.
• Tom contributes to the success of the team on a regular basis.
• Ben isn’t concerned about who gets the credit, just that the task gets accomplished.
• Mary is a team player and understands how to help others in times of need.
• Peter is the consummate team player.
Negative review
• Bill does not assist his teammates as required.
• Ryan holds on to too much and does not delegate to his team effectively.
• Bryan focuses on getting his own work accomplished, but does not take the time to help
those members of his team who are struggling to keep up.
• Peter was very good at teamwork when he was just a member of the team, now that he is
in a supervisory role, Peter has lost much of those teamwork skills.
• Lyle works with the team well when his own projects are coming due and he needs help,
but once those are accomplished, he does not frequently help others on their projects.
Job Performance Evaluation Form
Page 11
12. III.Top 12 methods for enterprise data architect performance
appraisal:
1.Management by Objectives (MBO) Method
This is one of the best methods for the judgment of an employee's performance, where the
managers and employees set a particular objective for employees and evaluate their performance
periodically. After the goal is achieved, the employees are also rewarded according to the results.
This performance appraisal method of management by objectives depends on accomplishing the
goal rather than how it is accomplished.
-----------------------------
MBO Features
MBO emphasizes participatively set goals that are tangible, verifiable and measurable.
MBO focuses attention on what must be accomplished (goals) rather than how it is to be
accomplished (methods).
MBO, by concentrating on key result areas translates the abstract philosophy of
management into concrete phraseology. The technique can be put to general use (non-
specialist technique). Further it is “a dynamic system which seeks to integrate the company's
Job Performance Evaluation Form
Page 12
13. need to clarify and achieve its profit and growth targets with the manager's need to contribute
and develop himself”.
MBO is a systematic and rational technique that allows management to attain maximum
results from available resources by focusing on achievable goals. It allows the subordinate
plenty of room to make creative decisions on his own.
-----------------------------
2.Critical Incident Method
In this method, the manager writes down the positive and negative behavioral performance of the
employees. This is done throughout the performance period and the final report is submitted as
the assessment of the employees. This method helps employees in managing their performance
and improves the quality of their work.
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Disadvantages of critical Incident
This method suffers however from the following limitations:
• Critical incidents technique of evaluation is applied to evaluate the performance of superiors
rather than of peers of subordinates.
• Negative incidents may be more noticeable than positive incidents.
• It results in very close supervision which may not be liked by the employee.
• The recording of incidents may be a chore for the manager concerned, who may be too busy or
forget to do it.
• The supervisors have a tendency to unload a series of complaints about incidents during an
annual performance review session.
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3.Behaviorally Anchored Rating Scales (BARS)
The BARS method is used to describe a rating of the employee's performance which focuses on
the specific behavior as indicators of effective and ineffective performance. This method is
usually a combination of two other methods namely, the rating scale and critical incident
technique of employee evaluation.
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Rating scales for BARs
Each behavior can rate at one of 7 scales as follows (you can set scales depend on your
requirements)
• Extremely poor (1 points)
• Poor (2 points)
• Below average (3 points)
• Average (4 points)
• Above average (5 points)
• Good (6 points)
• Extremely good (7 points)
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4.Behavioral Observation Scales (BOS)
It is defined as the frequency rating of critical incidents which the employee has performed over
a specific duration in the organization. It was developed because methods like graphic rating
scales and behaviorally anchored rating scales (BARS) depend on vague judgments made by the
supervisors about employees.
-----------------------------
5.360 Degree Performance Appraisal Method
The definition of this performance evaluation method is that, it is a system or process wherein
the employees receive some performance feedback examples, which are anonymous and
confidential from co-workers. This process is conducted by managers and subordinates who,
through 360 degrees, measure certain factors about the employees. These are behavior and
competence, skills such as listening, planning and goal-setting, teamwork, character, and
leadership effectiveness.
-----------------------------
Advantages of 360 degree appraisal
• Offer a more comprehensive view towards the performance of employees.
• Improve credibility of performance appraisal.
• Such colleague’s feedback will help strengthen self-development.
• Increases responsibilities of employees to their customers.
• The mix of ideas can give a more accurate assessment.
• Opinions gathered from lots of staff are sure to be more persuasive.
• Not only manager should make assessments on its staff performance but other colleagues
should do, too.
• People who undervalue themselves are often motivated by feedback from others.
• If more staff takes part in the process of performance appraisal, the organizational culture of the
company will become more honest.
-----------------------------
6.Checklist and Weighted Checklist Method
The checklist method comprises a list of set objectives and statements about the employee's
behavior. For example, leadership skills, on-time delivery, innovation, etc. If the appraiser
believes that the employee possesses the trait mentioned in the checklist, he puts a tick in front of
it. If he thinks the employee doesn't have a particular trait he will leave it blank and mentions
about it in the improvement column. Weighted checklist is a variation of the checklist method
where a value is allotted to each question. The value of each question can differ based on its
importance. The total score from the checklist is taken into consideration for evaluating the
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15. employee's performance. It poses a strong threat of bias on the appraiser's end. Though this
method is highly time-consuming and complex, it is widely used for performance evaluation.
-----------------------------
Advantages and disadvantages of weighted checklist
• This method help the manager in evaluation of the performance of the employee.
• The rater may be biased in distinguishing the positive and negative questions. He may assign
biased weights to the questions.
• This method also is expensive and time consuming.
• It becomes difficult for the manager to assemble, analyze and weigh a number of statements
about the employee’s characteristics, contributions and behaviors.
-----------------------------
7.Graphic Rating Scale Method
Graphic rating scale is one of the most frequently used performance evaluation methods. A
simple printed form enlists the traits of the employees required for completing the task
efficiently. They are then rated based on the degree to which an employee represents a particular
trait that affects the quantity and quality of work. A rating scale is adopted and implemented for
judging each trait of the employee. The merit of using this method is that it is easy to calculate
the rating. However, a major drawback of this method is that each characteristic is given equal
weight and the evaluation may be subjective.
-----------------------------
Advantages and Disadvantage of the rating scales
Advantages of the rating scales
• Graphic rating scales are less time consuming to develop.
• They also allow for quantitative comparison.
Disadvantages of the rating scales
• Different supervisors will use the same graphic scales in slightly different ways.
• One way to get around the ambiguity inherent in graphic rating scales is to use behavior based
scales, in which specific work related behaviors are assessed.
• More validity comparing workers ratings from a single supervisor than comparing two workers
who were rated by different supervisors.
-----------------------------
8.Comparative Evaluation Method
Two ways are used to make a comparative evaluation, namely, the simple ranking method and
the paired comparison method. In the simple or straight ranking method the employee is rated by
the evaluator on a scale of best to worst. However, the evaluator may be biased and may not
judge the overall performance effectively in the absence of fixed criteria. This kind of evaluation
may be more opinion-based than fact-based.
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16. Under the paired comparison method, the overall performance of one individual is directly
compared with that of the other on the basis of a common criterion. This comparison is all
evasive and not job-specific. While some employees emerge as clear front runners, there are
others who seem to be lagging behind. This is not a popular evaluation system as employers do
not want to encourage discrimination. This is useful in companies which have a limited number
of promotions or funds.
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Steps to conduct paired comparison analysis
• List the options you will compare (elements as A, B, C, D, E for example).
• Create a table 6 rows and 7 column.
• Write down option to column and row; A to row second, cell first from left and A to row first,
cell second from left; B to row third, cell first from left and B to row first, cell third from left etc;
column seventh is total point.
• Identify importance from 0 (no difference) to 3 (major difference).
• Compare element “A” to B, C, D, E and place “point” at each cell.
• Finally, consolidate the results by adding up the total of all the values for each of the options.
You may want to convert these values into a percentage of the total score.
-----------------------------
9.Forced Choice Method
In this method, the appraiser is asked to choose from two pairing statements which may appear
equally positive and negative. However, the statements dictate the performance of the employee.
An excellent example of this can be "works harder" and "works smarter". The appraiser selects a
statement without having knowledge of the favorable or the unfavorable one. This method works
in companies where the appraiser shows a tendency to under-evaluate or over-evaluate the
employees. Also, it is very costly to implement and does not serve the purpose of developing the
employees. It can also frustrate the appraiser as he does not know which is the right option.
-----------------------------
10.Forced Distribution Method
In this method, the appraiser rates employees according to a specific distribution. For example,
out of a set of 5 employees, 2 will get evaluated as high, 2 will get evaluated as average while 1
will be in the low category. This method has several benefits as it tries to eliminate the leniency
and central tendency of the appraiser. However, its biggest drawback is the fact that it
encourages discrimination among the employees. Another major problem with this method is
that it dictates that there will be forced distribution of grades even when all the employees are
doing a good job.
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Advantages and disadvantages of forced Ranking
Advantages:
• They force reluctant managers to make difficult decisions and identify the most and least
talented members of the work group.
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17. • They create and sustain a high performance culture in which the workforce continuously
improves.
Disadvantages
• They increase unhealthy cut-throat competitiveness;
• They discourage collaboration and teamwork;
• They harm morale;
• They are legally suspect giving rise to age discrimination cases.
-----------------------------
11.Essay Evaluation Method
In the essay method of evaluation the appraiser writes an elaborate statement about the employee
who is being evaluated. He mentions the employee's strengths and weaknesses. He also suggests
ways to improve his performance and appreciates the good qualities. This essay can be prepared
by the appraiser alone or together with the employee. As the criteria for evaluation is not defined,
it helps the appraiser to focus on the areas that actually need improvement. This open-ended
method accords flexibility and eliminates rigidity which is observed in criteria-driven
evaluations. However, it is a highly time-consuming and subjective method, and may not
necessarily work for the benefit of the organization.
-----------------------------
Essay evaluation is a non-quantitative technique
This method is advantageous in at least one sense, i.e., the essay provides a good deal of
information about the employee and also reveals more about the evaluator. The essay evaluation
method however, suffers from the following limitations:
It is highly subjective; the supervisor may write a biased essay. The employees who are
sycophants will be evaluated more favorably then other employees.
Some evaluators may be poor in writing essays on employee performance. Others may be
superficial in explanation and use flowery language which may not reflect the actual
performance of the employee. It is very difficult to find effective writers nowadays.
The appraiser is required to find time to prepare the essay. A busy appraiser may write
the essay hurriedly without properly assessing the actual performance of the worker. On the
other hand, appraiser takes a long time, this becomes uneconomical from the view point of the
firm, because the time of the evaluator (supervisor) is costly.
12.Performance Test and Observation Method
This method deals with testing the knowledge or skills of the employees. It can be implemented
in the form of a written test or can be based on the actual presentation of skills. The test must be
conceived by the human resources department and conducted by a reliable evaluator who has in-
depth knowledge about the field of the test. There can be bias if the performance is evaluated on
the presentation of skills. However, a written test can be a reliable yardstick to measure the
knowledge. Tests will also enable the management to check the potential of employees.
However, if the human resources department decides to outsource the compilation of the test, it
may incur additional cost for the organization.
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18. Fields/positions related to performance appraisal:
The above performance appraisal can be used for fields as:
construction, manufacturing, healthcare, non profit, advertising, agile, architecture, automotive,
agency, budget, building, business development, consulting, communication, clinical research,
design, software development, product development, interior design, web development,
engineering, education, events, electrical, exhibition, energy, ngo, finance, fashion, green card,
oil gas, hospital, it, marketing, media, mining, nhs, non technical, oil and gas, offshore,
pharmaceutical, real estate, retail, research, human resources, telecommunications, technology,
technical, senior, digital, software, web, clinical, hr, infrastructure, business, erp, creative, ict,
hvac, sales, quality management, uk, implementation, network, operations, architectural,
environmental, crm, website, interactive, security, supply chain, logistics, training, project
management, administrative management…
The above performance appraisal also can be used for job title levels:
entry level, junior, senior, assistant, associate, administrator, clerk, coordinator, consultant,
controller, director, engineer, executive, leader, manager, officer, specialist, supervisor, VP…
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