Data pipelines observability: OpenLineage & MarquezJulien Le Dem
This document discusses OpenLineage and Marquez, which aim to provide standardized metadata and data lineage collection for data pipelines. OpenLineage defines an open standard for collecting metadata as data moves through pipelines, similar to metadata collected by EXIF for images. Marquez is an open source implementation of this standard, which can collect metadata from various data tools and store it in a graph database for querying lineage and understanding dependencies. This collected metadata helps with tasks like troubleshooting, impact analysis, and understanding how data flows through complex pipelines over time.
Open core summit: Observability for data pipelines with OpenLineageJulien Le Dem
This document discusses Open Lineage and the Marquez project for collecting metadata and data lineage information from data pipelines. It describes how Open Lineage defines a standard model and protocol for instrumentation to collect metadata on jobs, datasets, and runs in a consistent way. This metadata can then provide context on the data source, schema, owners, usage, and changes. The document outlines how Marquez implements the Open Lineage standard by defining entities, relationships, and facets to store this metadata and enable use cases like data governance, discovery, and debugging. It also positions Marquez as a centralized but modular framework to integrate various data platforms and extensions like Datakin's lineage analysis tools.
Data integration combines data from disparate sources into a data warehouse using extract, transform, and load (ETL) processes. It involves discovering, cleaning, monitoring, transforming, and delivering data from various sources. Ensuring data quality is critical through checks, constraints, and consistency tests. Performance is improved through cost-based job scheduling, incremental loads, parallelization, indexing, and compute keys. The process is monitored through runtime statistics, timelines, schema and relation sizes, and index usage.
SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications used for extracting, transforming, and loading (ETL) data. SSIS packages contain control flows and data flows to organize tasks for data migration. SSIS provides tools for loading data, transforming data types, and splitting data into training and testing sets for data mining models. It includes data mining transformations in the control flow and data flow environments to prepare and analyze text data for classification, clustering, and association models.
Professional Recycling - SSIS Custom Control Flow Components With Visual Stud...Wolfgang Strasser
This document discusses creating custom control flow components for SQL Server Integration Services (SSIS) using Visual Studio Community. It covers the development environment, creating a new custom component project, deploying the component, accessing variables, debugging, internationalization, and best practices like automated builds and versioning. The presenter demonstrates creating a simple component that reads and writes variables, validating properties, and handling events.
Mapping Data Flows Training deck Q1 CY22Mark Kromer
Mapping data flows allow for code-free data transformation at scale using an Apache Spark engine within Azure Data Factory. Key points:
- Mapping data flows can handle structured and unstructured data using an intuitive visual interface without needing to know Spark, Scala, Python, etc.
- The data flow designer builds a transformation script that is executed on a JIT Spark cluster within ADF. This allows for scaled-out, serverless data transformation.
- Common uses of mapping data flows include ETL scenarios like slowly changing dimensions, analytics tasks like data profiling, cleansing, and aggregations.
The document summarizes topics that were covered in an SQL community meeting in December 2018, including tuning queries for performance, understanding execution plans, using performance monitoring tools, and troubleshooting queries. Key areas discussed were the SQL query processing steps, factors that affect performance like the buffer cache hit ratio, and methods for analyzing execution plans and data access operators like table scans and index seeks.
The document describes an OLTP database created for a construction company to store ongoing and closed project data in third normal form. An ETL process was developed using SSIS to load data from Excel spreadsheets and XML files into the database tables. This ETL package was combined with database backup, shrink, and index rebuild processes into a single job scheduled to run regularly via SQL Server Agent. The document includes diagrams and details of the database structure and various SSIS packages developed for the ETL load processes.
Data pipelines observability: OpenLineage & MarquezJulien Le Dem
This document discusses OpenLineage and Marquez, which aim to provide standardized metadata and data lineage collection for data pipelines. OpenLineage defines an open standard for collecting metadata as data moves through pipelines, similar to metadata collected by EXIF for images. Marquez is an open source implementation of this standard, which can collect metadata from various data tools and store it in a graph database for querying lineage and understanding dependencies. This collected metadata helps with tasks like troubleshooting, impact analysis, and understanding how data flows through complex pipelines over time.
Open core summit: Observability for data pipelines with OpenLineageJulien Le Dem
This document discusses Open Lineage and the Marquez project for collecting metadata and data lineage information from data pipelines. It describes how Open Lineage defines a standard model and protocol for instrumentation to collect metadata on jobs, datasets, and runs in a consistent way. This metadata can then provide context on the data source, schema, owners, usage, and changes. The document outlines how Marquez implements the Open Lineage standard by defining entities, relationships, and facets to store this metadata and enable use cases like data governance, discovery, and debugging. It also positions Marquez as a centralized but modular framework to integrate various data platforms and extensions like Datakin's lineage analysis tools.
Data integration combines data from disparate sources into a data warehouse using extract, transform, and load (ETL) processes. It involves discovering, cleaning, monitoring, transforming, and delivering data from various sources. Ensuring data quality is critical through checks, constraints, and consistency tests. Performance is improved through cost-based job scheduling, incremental loads, parallelization, indexing, and compute keys. The process is monitored through runtime statistics, timelines, schema and relation sizes, and index usage.
SQL Server Integration Services (SSIS) is a platform for data integration and workflow applications used for extracting, transforming, and loading (ETL) data. SSIS packages contain control flows and data flows to organize tasks for data migration. SSIS provides tools for loading data, transforming data types, and splitting data into training and testing sets for data mining models. It includes data mining transformations in the control flow and data flow environments to prepare and analyze text data for classification, clustering, and association models.
Professional Recycling - SSIS Custom Control Flow Components With Visual Stud...Wolfgang Strasser
This document discusses creating custom control flow components for SQL Server Integration Services (SSIS) using Visual Studio Community. It covers the development environment, creating a new custom component project, deploying the component, accessing variables, debugging, internationalization, and best practices like automated builds and versioning. The presenter demonstrates creating a simple component that reads and writes variables, validating properties, and handling events.
Mapping Data Flows Training deck Q1 CY22Mark Kromer
Mapping data flows allow for code-free data transformation at scale using an Apache Spark engine within Azure Data Factory. Key points:
- Mapping data flows can handle structured and unstructured data using an intuitive visual interface without needing to know Spark, Scala, Python, etc.
- The data flow designer builds a transformation script that is executed on a JIT Spark cluster within ADF. This allows for scaled-out, serverless data transformation.
- Common uses of mapping data flows include ETL scenarios like slowly changing dimensions, analytics tasks like data profiling, cleansing, and aggregations.
The document summarizes topics that were covered in an SQL community meeting in December 2018, including tuning queries for performance, understanding execution plans, using performance monitoring tools, and troubleshooting queries. Key areas discussed were the SQL query processing steps, factors that affect performance like the buffer cache hit ratio, and methods for analyzing execution plans and data access operators like table scans and index seeks.
The document describes an OLTP database created for a construction company to store ongoing and closed project data in third normal form. An ETL process was developed using SSIS to load data from Excel spreadsheets and XML files into the database tables. This ETL package was combined with database backup, shrink, and index rebuild processes into a single job scheduled to run regularly via SQL Server Agent. The document includes diagrams and details of the database structure and various SSIS packages developed for the ETL load processes.
The document describes Data Transfer Application V2, which allows for complex selective refreshing of data from a database with minimal manual interaction. It saves time during reprocessing by reducing the amount of refreshed data needed. Key improvements over the previous version include added automation through configurable jobs, increased flexibility in selecting tables and columns, and improved logging and error handling. The next steps are to use the new application for an August database refresh.
Gopi has over 3 years of experience implementing data warehousing projects with Teradata. He has a B.Tech in Electrical and Electronics Engineering from Prakasam Engineering College. His skills include loading data into Teradata from flat files using FastLoad scripts and working with Teradata utilities like BTEQ, Fast Load, Multi Load, and Tpump. He has worked on two projects - a financial data reporting system for Black hawk Network and a customer enterprise data warehouse for Verizon UK, where he was responsible for ETL development, scripting, query optimization, and more.
Azure Data Factory Data Flows Training v005Mark Kromer
Mapping Data Flow is a new feature of Azure Data Factory that allows building data transformations in a visual interface without code. It provides a serverless, scale-out transformation engine for processing big data with unstructured requirements. Mapping Data Flows can be authored and designed visually, with transformations, expressions, and results previews, and then operationalized with Data Factory scheduling, monitoring, and control flow.
This session provides an introduction to using SSIS. This is an update to my older presentation on the topic: http://www.slideshare.net/rmaclean/sql-server-integration-services-2631027
The document provides an overview of SQL Server including:
- The architecture including system databases like master, model, msdb, and tempdb.
- Recovery models like full, bulk-logged, and simple.
- Backup and restore options including full, differential, transaction log, and file group backups.
- T-SQL system stored procedures for administration tasks.
- SQL commands and functions.
- SQL Agent jobs which are scheduled tasks consisting of steps to perform automated tasks.
The document discusses the design of a relational database system called the Supersite Relational Data System (SRDS) that would integrate air quality monitoring data from multiple Supersite projects and auxiliary datasets for cross-site analysis. It proposes using a star schema with dimensions for time, location, parameter, and method to facilitate querying and comparisons across different monitoring sites and projects. The schema would be extended as needed based on user requirements and consensus-building within the Supersite working groups.
The control flow manages the execution of tasks and containers in an SSIS package. It contains control flow tasks, containers, and precedence constraints. There are three primary control flow objects - tasks that perform jobs, containers that group tasks and containers, and constraints that define execution order. A control flow task performs operations like sending emails or copying files, and completes as succeeded or failed.
This article provides tips for improving the performance of Microsoft Access 2007 applications. Some key tips include splitting the database into separate application and data files, compacting the database regularly, limiting fields returned in queries, adding indexes to fields used for criteria or joins, and using temporary tables to store intermediate query results rather than running the same queries repeatedly. Following these tips can help optimize database, query, form and report performance.
The document discusses Extract, Transform, Load (ETL) processes. It defines extract as reading data from a database, transform as converting extracted data into a form suitable for another database, and load as writing transformed data into the target database. It then lists several common ETL tools and databases they can connect to.
SQL Server Integration Services (SSIS) is a platform for building extract, transform, and load (ETL) packages and other data integration and workflow tasks. It includes graphical tools and wizards to design packages, as well as utilities to run, debug, and deploy packages. Key components of SSIS include control flow tasks, data flows, variables, logging, and support for transactions and restarting failed packages.
Apache Spark for Library Developers with William Benton and Erik ErlandsonDatabricks
As a developer, data engineer, or data scientist, you’ve seen how Apache Spark is expressive enough to let you solve problems elegantly and efficient enough to let you scale out to handle more data. However, if you’re solving the same problems again and again, you probably want to capture and distribute your solutions so that you can focus on new problems and so other people can reuse and remix them: you want to develop a library that extends Spark.
You faced a learning curve when you first started using Spark, and you’ll face a different learning curve as you start to develop reusable abstractions atop Spark. In this talk, two experienced Spark library developers will give you the background and context you’ll need to turn your code into a library that you can share with the world. We’ll cover: Issues to consider when developing parallel algorithms with Spark, Designing generic, robust functions that operate on data frames and datasets, Extending data frames with user-defined functions (UDFs) and user-defined aggregates (UDAFs), Best practices around caching and broadcasting, and why these are especially important for library developers, Integrating with ML pipelines, Exposing key functionality in both Python and Scala, and How to test, build, and publish your library for the community.
We’ll back up our advice with concrete examples from real packages built atop Spark. You’ll leave this talk informed and inspired to take your Spark proficiency to the next level and develop and publish an awesome library of your own.
Andy Keller and Dave Shepperton, Traction Software. Traction User Group, Oct 14 2010, Newport RI. TUG 2010 Newport slides, agenda and more see www.TractionSoftware.com
ETL is a process that involves extracting data from multiple sources, transforming it to fit operational needs, and loading it into a data warehouse. It provides a method of moving data from various source systems into a data warehouse to enable complex business analysis. The ETL process consists of extraction, which gathers and cleanses raw data from source systems, transform, which prepares the data for the data warehouse through steps like validation and standardization, and load, which stores the transformed data in the data warehouse. ETL tools automate and simplify the ETL process and provide advantages like faster development, metadata management, and performance optimization.
This document summarizes a webinar about Open Services for Lifecycle Collaboration (OSLC) and data integration. It introduces the presenter Axel Reichwein and his company Koneksys, which helps organizations create data integration solutions. It discusses challenges of distributed engineering data from different sources and the benefits of data integration. Key concepts discussed include using URLs, HTTP, and RDF to create a web of linked data. OSLC standards provide APIs to access and link data from different sources. This allows building mashup applications to search, visualize, and link engineering information across distributed systems.
A Deep Dive into Stateful Stream Processing in Structured Streaming with Tath...Databricks
Stateful processing is one of the most challenging aspects of distributed, fault-tolerant stream processing. The DataFrame APIs in Structured Streaming make it very easy for the developer to express their stateful logic, either implicitly (streaming aggregations) or explicitly (mapGroupsWithState). However, there are a number of moving parts under the hood which makes all the magic possible. In this talk, I am going to dive deeper into how stateful processing works in Structured Streaming.
In particular, I’m going to discuss the following.
• Different stateful operations in Structured Streaming
• How state data is stored in a distributed, fault-tolerant manner using State Stores
• How you can write custom State Stores for saving state to external storage systems.
H:\Facts\Power Point\Role Models & Leadersguest91496f
Selena Quintanilla-Perez was a Mexican American singer who began her career at a young age by joining her family's band, Selena y Los Dinos. She became known in Texas in the late 1980s and earned several awards, including Female Vocalist of the Year from the Tejano Music Awards. Her 1991 hit "Buenos Amigos" reached number one on the Billboard Latin charts and helped her breakthrough. She was fluent in both English and Spanish, which allowed her to communicate with audiences on both sides of the border. Tragically, at the age of 23 while working on her first crossover album, she was shot and killed by the former president of her fan club in 1995.
Use this pathfinder to learn how to create a manage a budget. Numerous print and online resources are included. Check out the free online courses and sample budget worksheet
The document describes Data Transfer Application V2, which allows for complex selective refreshing of data from a database with minimal manual interaction. It saves time during reprocessing by reducing the amount of refreshed data needed. Key improvements over the previous version include added automation through configurable jobs, increased flexibility in selecting tables and columns, and improved logging and error handling. The next steps are to use the new application for an August database refresh.
Gopi has over 3 years of experience implementing data warehousing projects with Teradata. He has a B.Tech in Electrical and Electronics Engineering from Prakasam Engineering College. His skills include loading data into Teradata from flat files using FastLoad scripts and working with Teradata utilities like BTEQ, Fast Load, Multi Load, and Tpump. He has worked on two projects - a financial data reporting system for Black hawk Network and a customer enterprise data warehouse for Verizon UK, where he was responsible for ETL development, scripting, query optimization, and more.
Azure Data Factory Data Flows Training v005Mark Kromer
Mapping Data Flow is a new feature of Azure Data Factory that allows building data transformations in a visual interface without code. It provides a serverless, scale-out transformation engine for processing big data with unstructured requirements. Mapping Data Flows can be authored and designed visually, with transformations, expressions, and results previews, and then operationalized with Data Factory scheduling, monitoring, and control flow.
This session provides an introduction to using SSIS. This is an update to my older presentation on the topic: http://www.slideshare.net/rmaclean/sql-server-integration-services-2631027
The document provides an overview of SQL Server including:
- The architecture including system databases like master, model, msdb, and tempdb.
- Recovery models like full, bulk-logged, and simple.
- Backup and restore options including full, differential, transaction log, and file group backups.
- T-SQL system stored procedures for administration tasks.
- SQL commands and functions.
- SQL Agent jobs which are scheduled tasks consisting of steps to perform automated tasks.
The document discusses the design of a relational database system called the Supersite Relational Data System (SRDS) that would integrate air quality monitoring data from multiple Supersite projects and auxiliary datasets for cross-site analysis. It proposes using a star schema with dimensions for time, location, parameter, and method to facilitate querying and comparisons across different monitoring sites and projects. The schema would be extended as needed based on user requirements and consensus-building within the Supersite working groups.
The control flow manages the execution of tasks and containers in an SSIS package. It contains control flow tasks, containers, and precedence constraints. There are three primary control flow objects - tasks that perform jobs, containers that group tasks and containers, and constraints that define execution order. A control flow task performs operations like sending emails or copying files, and completes as succeeded or failed.
This article provides tips for improving the performance of Microsoft Access 2007 applications. Some key tips include splitting the database into separate application and data files, compacting the database regularly, limiting fields returned in queries, adding indexes to fields used for criteria or joins, and using temporary tables to store intermediate query results rather than running the same queries repeatedly. Following these tips can help optimize database, query, form and report performance.
The document discusses Extract, Transform, Load (ETL) processes. It defines extract as reading data from a database, transform as converting extracted data into a form suitable for another database, and load as writing transformed data into the target database. It then lists several common ETL tools and databases they can connect to.
SQL Server Integration Services (SSIS) is a platform for building extract, transform, and load (ETL) packages and other data integration and workflow tasks. It includes graphical tools and wizards to design packages, as well as utilities to run, debug, and deploy packages. Key components of SSIS include control flow tasks, data flows, variables, logging, and support for transactions and restarting failed packages.
Apache Spark for Library Developers with William Benton and Erik ErlandsonDatabricks
As a developer, data engineer, or data scientist, you’ve seen how Apache Spark is expressive enough to let you solve problems elegantly and efficient enough to let you scale out to handle more data. However, if you’re solving the same problems again and again, you probably want to capture and distribute your solutions so that you can focus on new problems and so other people can reuse and remix them: you want to develop a library that extends Spark.
You faced a learning curve when you first started using Spark, and you’ll face a different learning curve as you start to develop reusable abstractions atop Spark. In this talk, two experienced Spark library developers will give you the background and context you’ll need to turn your code into a library that you can share with the world. We’ll cover: Issues to consider when developing parallel algorithms with Spark, Designing generic, robust functions that operate on data frames and datasets, Extending data frames with user-defined functions (UDFs) and user-defined aggregates (UDAFs), Best practices around caching and broadcasting, and why these are especially important for library developers, Integrating with ML pipelines, Exposing key functionality in both Python and Scala, and How to test, build, and publish your library for the community.
We’ll back up our advice with concrete examples from real packages built atop Spark. You’ll leave this talk informed and inspired to take your Spark proficiency to the next level and develop and publish an awesome library of your own.
Andy Keller and Dave Shepperton, Traction Software. Traction User Group, Oct 14 2010, Newport RI. TUG 2010 Newport slides, agenda and more see www.TractionSoftware.com
ETL is a process that involves extracting data from multiple sources, transforming it to fit operational needs, and loading it into a data warehouse. It provides a method of moving data from various source systems into a data warehouse to enable complex business analysis. The ETL process consists of extraction, which gathers and cleanses raw data from source systems, transform, which prepares the data for the data warehouse through steps like validation and standardization, and load, which stores the transformed data in the data warehouse. ETL tools automate and simplify the ETL process and provide advantages like faster development, metadata management, and performance optimization.
This document summarizes a webinar about Open Services for Lifecycle Collaboration (OSLC) and data integration. It introduces the presenter Axel Reichwein and his company Koneksys, which helps organizations create data integration solutions. It discusses challenges of distributed engineering data from different sources and the benefits of data integration. Key concepts discussed include using URLs, HTTP, and RDF to create a web of linked data. OSLC standards provide APIs to access and link data from different sources. This allows building mashup applications to search, visualize, and link engineering information across distributed systems.
A Deep Dive into Stateful Stream Processing in Structured Streaming with Tath...Databricks
Stateful processing is one of the most challenging aspects of distributed, fault-tolerant stream processing. The DataFrame APIs in Structured Streaming make it very easy for the developer to express their stateful logic, either implicitly (streaming aggregations) or explicitly (mapGroupsWithState). However, there are a number of moving parts under the hood which makes all the magic possible. In this talk, I am going to dive deeper into how stateful processing works in Structured Streaming.
In particular, I’m going to discuss the following.
• Different stateful operations in Structured Streaming
• How state data is stored in a distributed, fault-tolerant manner using State Stores
• How you can write custom State Stores for saving state to external storage systems.
H:\Facts\Power Point\Role Models & Leadersguest91496f
Selena Quintanilla-Perez was a Mexican American singer who began her career at a young age by joining her family's band, Selena y Los Dinos. She became known in Texas in the late 1980s and earned several awards, including Female Vocalist of the Year from the Tejano Music Awards. Her 1991 hit "Buenos Amigos" reached number one on the Billboard Latin charts and helped her breakthrough. She was fluent in both English and Spanish, which allowed her to communicate with audiences on both sides of the border. Tragically, at the age of 23 while working on her first crossover album, she was shot and killed by the former president of her fan club in 1995.
Use this pathfinder to learn how to create a manage a budget. Numerous print and online resources are included. Check out the free online courses and sample budget worksheet
Use this pathfinder to find books and information on social media websites and platforms such as Facebook, Twitter, Pinterest, and blogging. It also includes general information and information on marketing and job searching.
- The document provides an introduction to using an online learning portal, including how to navigate courses, topics, and blocks within the portal.
- It outlines how to create an account, log in, find and access specific courses, and describes the basic navigation features within courses like breadcrumbs, topics, and blocks.
- Instructions are given on how to view different topics, collapse topics to focus on one, and use the "Jump to" menu to select other topics.
Apresentação Câmara Técnica Áreas Verdes 2016copelli
O documento descreve o Programa de Monitoramento da Cobertura Vegetal do Rio de Janeiro, que mapeia as áreas de floresta remanescente na cidade utilizando sensoriamento remoto e levantamentos de campo. O programa identificou que 29% da área da cidade ainda possui cobertura vegetal nativa, enquanto as áreas urbanizadas correspondem a 66% do território. As principais transformações entre 2010-2014 incluíram a conversão de florestas e brejos para uso urbano e solo exposto.
The document discusses the expansion of western civilization and global trade networks from the 15th century onward. It describes how technological developments like the compass and mapmaking enabled longer ocean voyages. Countries like Portugal sought to protect their commercial interests by establishing forts along trade routes. Explorers like Columbus and Magellan opened up sea routes connecting Europe, Africa, Asia, and the Americas, integrating these regions into a growing global economy. Over time, more areas and peoples around the world were incorporated into the expanding webs of trade, leading to profound cultural and economic changes on a global scale.
The document discusses the creation of logos, propaganda posters, and visuals for political parties. It includes sections from multiple students. One student created a green party focused on environmental issues with a simple name-based logo in green and blue. Another created a capitalist party with propaganda posters to attract voters and change views. A third created an international neutral party promoting equality with a logo and posters sending that message.
Students explore how media uses emotional appeals to influence consumer identities and behavior. They analyze how audiences are manipulated into being consumers through advertising and consumerism. Specifically, students use The Walt Disney Company as a case study to examine how highly emotional Disney movies spark sympathy in children, which is then transferred through marketing strategies to influence parents' consumer habits by merchandising Disney products.
HRGO Recruitment is a UK-based recruitment agency established in 1957 with 60 locations throughout the UK and Europe. They have specialized divisions and a turnover of £90 million in 2009, making them one of the top 45 recruitment agencies in the UK. They offer a complete service package including account management, an extensive candidate pool, and a proven track record of supplying volume contracts with a commitment to customer and candidate care.
Jonah Probelle is a multitalented engineer, businessman, and entrepreneur with expertise in various areas including chip design, digital signal processing, intellectual property, technology marketing, and technical writing. He has experience with topics such as processor architecture, FPGA design, verification methodology, timing analysis, and more. His company, YAP IP, designs and licenses processor cores including an advanced 32-bit RISC-DSP processor with SIMD extensions targeted towards Linux systems.
Investment Management: Once you have a firm background on the financial market, and have chosen a personal investment path, these resources will assist you with managing your assets. By continuing your financial education, staying up to date on market trends and by following industry news, you will increase your opportunity for financial success.
ACK Travel is a leading corporate travel management company in India that provides integrated travel solutions. Their global technology infrastructure allows corporations to analyze travel data and maximize efficiency and return on investment. ACK Travel aims to anticipate customer needs and respond with excellent service. They were founded in 2006 and have experienced consistent growth through their customer-focused and service-oriented approach. Services include domestic and international air, rail, bus, taxi, hotels, visas, holidays, and foreign exchange. Special offers provide additional value to customers. ACK Travel ensures the best rates through direct connections with airlines and well-trained staff.
This document contains summaries of multiple paragraphs from texts about European expansion and the development of a global economy between the 15th-18th centuries. It discusses how technological advancements allowed for long-distance ocean voyages, enabling Portugal and Spain to explore and establish trade networks and colonies. It also summarizes how other European powers like the Dutch and British later established private companies to enter and compete in Asian and American trade, integrating more regions and populations into a growing global economic system dominated by Western Europe.
Here are a list of local and state organizations (Philadelphia, Philadelphia region, and Pennsylvania) that can assist you on your journey to entrepreneurship.
La semana cultural incluyó juegos y actividades artísticas para los niños. Los padres ayudaron en un evento de pintura el martes, donde los niños crearon sus propias obras. Los niños también disfrutaron de otros juegos el jueves.
The document discusses the four fundamental forces in the universe: gravitational, electromagnetic, weak nuclear, and strong nuclear forces. It provides details on each force, including their relative strengths and characteristics. The document then discusses applications of these fundamental forces to ordinary mechanical systems, focusing on friction forces. It outlines the laws of static and kinetic friction, defining coefficients of static and kinetic friction as the ratio of frictional force to normal force. In summary, the document provides an overview of fundamental forces and their applications to mechanical systems like friction.
Ringkasan dokumen tersebut adalah:
1. Dokumen tersebut membahas tentang penggunaan propaganda dan pengelolaan opini publik di era media sosial saat ini.
2. Metode propaganda yang dibahas antara lain propaganda tersembunyi, terbuka, agitasi, dan integrasi.
3. Dokumen juga membahas tentang perubahan proses pengaruh opini publik di era media sosial 2.0 dan 3.0.
How to tell an engaging and concise business storyStuart Collins
Often, presenters arrive at their conference or the rehearsal with an intention of what they want to communicate in mind. And it's great stuff! However, their talking points and visuals often obfuscate their intention. Have you ever been Powerpointed to death?
I've worked my company's employees and our customer presenters to pull out the intention of the speaker and turn busy slides and speaking tangents into a clear and powerful talk.
Given how important speaking engagements are to our goals, I'd like to offer one of the fundamental structures for telling an engaging and concise business story. This is the 4-point story. Use a 4-point story to establish the main points of what you wish to say. Pretty soon you can deliver a coherent and powerful talk that fulfills on what you set out to communicate.
I initially used these slides in a 60min workshop with local business owners in San Leandro, CA in 2016.
This document summarizes a business intelligence portfolio project for a simulated construction company. It includes details on an ETL solution built in SQL Server Integration Services to load data nightly from various sources into a SQL database. It also covers an OLAP cube with a partial snowflake structure created in SQL Server Analysis Services, including sample MDX queries and KPIs. Finally, it discusses reports deployed to SharePoint using SQL Server Reporting Services and PerformancePoint Services, including gauges, charts and dashboards. The overall goal was to build a BI solution to track, analyze and report on all aspects of the company's business using Microsoft SQL Server and SharePoint technologies.
This document provides an overview and samples of a business intelligence project using SQL Server Integration Services (SSIS), SQL Server Analysis Services (SSAS), and SQL Server Reporting Services (SSRS). It includes descriptions of ETL packages in SSIS to load and transform data, a cube with dimensions and calculations in SSAS, and sample MDX queries and reports. The goals are to track, analyze, and report on facets of a simulated construction company.
Syamali Ray is seeking a position applying their 7+ years of experience in information technology, with a focus on SAS programming. They have experience in SAS Base, SAS Graph, SAS Macro, SQL, and Microsoft Office. Their experience includes roles as a SAS consultant for several companies, developing reports and analyzing data. They have a bachelor's degree in mathematics and education from Calcutta University.
This document provides a summary of Maharshi Amin's professional experience and technical skills. He has over 10 years of experience developing software applications for the financial industry using technologies like Perl, Java, Sybase, and Informatica. His experience includes roles supporting trading, risk management, and regulatory reporting systems. He has strong skills in database design, application development, performance tuning, and leading development teams.
Varun has over 10 years of experience as an Oracle PL/SQL developer. He has extensive expertise in developing stored procedures, packages, triggers and performing performance tuning. Varun has worked on various projects involving data warehousing and ETL for companies like Fidelity Investments, Goldman Sachs, and Royal Bank of Scotland. His responsibilities included requirement analysis, testing, automating processes, and providing production support. Currently, he is a technical lead at Fidelity Investments where he monitors batches, enhances applications, and identifies performance improvements.
The document lists the key achievements of an individual including leading an upgrade of a large SAS grid from version 9.2 to 9.4, building a custom tool to extract column level lineage for SAS processes, and acting as a technical lead for various projects involving data landing, integration, modeling, and administration. It also notes achievements in standardizing solutions, designing operational databases, mentoring teammates, and consulting on data quality.
Rajeev kumar apache_spark & scala developerRajeev Kumar
Rajeev Kumar is an experienced Apache Spark and Scala developer based in Amsterdam, NL. He has over 8 years of experience working with big data technologies like Apache Spark, Scala, Java, Hadoop, and data integration tools. He is proficient in processing large structured and unstructured datasets to identify patterns and gain insights. His experience includes designing and developing Spark applications using Scala, ETL processes, data warehousing, and working with technologies like Hive, HDFS, MapReduce, Sqoop, Kafka and more.
Sivakumar has over 9 years of experience in data warehousing and ETL development using tools like Informatica and Teradata. He has extensive experience designing and developing ETL processes, performing testing, and collaborating with other teams on data migration projects for clients in various industries.
Sivakumar has over 9 years of experience in data warehousing and ETL development using tools like Informatica and Teradata. He has extensive experience designing and developing ETL processes for data migration, analytics projects for clients in various industries. His roles have included requirement analysis, mapping design, testing, performance tuning and managing project timelines.
1. The customer asked the author to build an analytical platform to store data in a database and perform statistical analysis from a front-end interface.
2. The author chose an SAP Sybase IQ column-store database to store data, the open-source R programming language to perform statistical analysis, and RStudio as the front-end interface.
3. The solution provided a simple way to load and query large amounts of data, automated running of statistical models, and could be deployed in the cloud.
1. The document describes building an analytical platform for a retailer by using open source tools R and RStudio along with SAP Sybase IQ database.
2. Key aspects included setting up SAP Sybase IQ as a column-store database for storage and querying of data, implementing R and RStudio for statistical analysis, and automating running of statistical models on new data.
3. The solution provided a low-cost platform capable of rapid prototyping of analytical models and production use for predictive analytics.
SQL Server Data Tools (SSDT) is a set of tools and services that integrate with Visual Studio to enable developers to work with SQL Server and SQL Azure databases directly from within Visual Studio. SSDT allows developers to manage database development lifecycles through features like schema comparison, data synchronization, edition and version targeting, and refactoring. SSDT uses DACPAC and BACPAC files to package and deploy database schemas and data between environments.
This document contains the resume of Rajat Goswami. It summarizes his contact information, career objective, skills, certifications, professional experience, and educational qualifications. His career objective is to contribute his knowledge and skills to help organizations grow. He has over 3 years of experience as a Datastage developer working with tools like Datastage, Oracle, and SQL. He is proficient in Linux, Windows, SQL, PL/SQL, and Autosys. His most recent role was as a Software Engineer Analyst at Capgemini working on ETL jobs and data warehouse maintenance and development. He has a Bachelor of Technology degree in Computer Science.
Cognos Framework Manager is a metadata modeling tool.Cognos Framework Manager provides the metadata model development environment for Cognos 8.A model is a business presentation of the information from one or more data sources. The model provides a business presentation of the metadata.The model is packaged and published for report authors and query users
Live online IT Training with MaxOnlineTraining.com is an easy, effective way to maximize your skills without the travel.
Call us at For any queries, please contact:
+1 940 440 8084 / +91 953 383 7156 TODAY to join our Online IT Training course & find out how Max Online Training.com can help you embark on an exciting and lucrative IT career.
Visit www.maxonlinetraining.com
This document provides a summary of an individual's skills and experience in data migration projects. The key points are:
1. The individual has over 7 years of experience in data extraction, transformation and loading using tools like SAP BODS, IBM Websphere Datastage, and SQL.
2. They have worked on international projects for clients in Germany, USA, Canada, UK, and Australia; and have experience in technologies like SQL Server, Oracle, SAP BO, SAP BODS.
3. Their roles include designing ETL processes, mapping data, implementing and optimizing extract-transform-load processes, and understanding business and technical requirements for data migration projects.
Kent E. Schweitzer has over 20 years of experience as an Oracle developer, database administrator, and team leader/manager. He has extensive experience with Oracle database administration, PL/SQL development, data warehousing, ETL processes, and automation of batch jobs. His background includes developing and supporting large data warehouse and reporting applications, performance tuning, and managing teams. He is currently a Vice President of Enterprise Data and Analytics at Wells Fargo, where he has worked on several projects involving data integration, reporting, and analytics.
The document contains a resume for Hari Krishna B summarizing his professional experience as a PL/SQL Developer working on software development and maintenance of web and client server applications. He has over 3 years of experience working with technologies like Oracle, PL/SQL, and SQL. His most recent role was as a Software Engineer at MetricStream Infotech India Pvt Ltd where he worked on projects involving compliance management, issue management, and GRC foundation for various clients.