Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
Today’s organisations require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lake is a new and increasingly popular way to store all of your data, structured and unstructured, in one, centralised repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
In this webinar, you will discover how AWS gives you fast access to flexible and low-cost IT resources, so you can rapidly scale and build your data lake that can power any kind of analytics such as data warehousing, clickstream analytics, fraud detection, recommendation engines, event-driven ETL, serverless computing, and internet-of-things processing regardless of volume, velocity and variety of data.
Learning Objectives:
• Discover how you can rapidly scale and build your data lake with AWS.
• Explore the key pillars behind a successful data lake implementation.
• Learn how to use the Amazon Simple Storage Service (S3) as the basis for your data lake.
• Learn about the new AWS services recently launched, Amazon Athena and Amazon Redshift Spectrum, that help customers directly query that data lake.
Banking Circle: Money Laundering Beware: A Modern Approach to AML with Machin...Neo4j
by Ruben Menke, Lead Data Scientist at Banking Circle
In this talk, Banking Circle will show how a modern computational method is essential in the fight against money laundering.
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
Standing Up an Effective Enterprise Data Hub -- Technology and BeyondCloudera, Inc.
Federal organizations increasingly are focused on creating environments that enable more data-driven decisions. Yet ensuring that all data is considered and is current, complete, and accurate is a tall order for most. To make data analytics meaningful to support real-world transformation, agency staff need business tools that provide user-friendly dashboards, on-demand reporting, and methods to manage efficiently the rise of voluminous and varied data sets and types commonly associated with big data. In most cases, existing systems are insufficient to support these requirements. Enter the enterprise data hub (EDH), a software architecture specifically designed to be a unified platform that can economically store unlimited data and enable diverse access to it at scale. Plan to attend this discussion to understand the key considerations to making an EDH the architectural center of your agency’s modern data strategy.
Data Architecture Best Practices for Advanced AnalyticsDATAVERSITY
Many organizations are immature when it comes to data and analytics use. The answer lies in delivering a greater level of insight from data, straight to the point of need.
There are so many Data Architecture best practices today, accumulated from years of practice. In this webinar, William will look at some Data Architecture best practices that he believes have emerged in the past two years and are not worked into many enterprise data programs yet. These are keepers and will be required to move towards, by one means or another, so it’s best to mindfully work them into the environment.
Data Architecture, Solution Architecture, Platform Architecture — What’s the ...DATAVERSITY
A solid data architecture is critical to the success of any data initiative. But what is meant by “data architecture”? Throughout the industry, there are many different “flavors” of data architecture, each with its own unique value and use cases for describing key aspects of the data landscape. Join this webinar to demystify the various architecture styles and understand how they can add value to your organization.
Today’s organisations require a data storage and analytics solution that offers more agility and flexibility than traditional data management systems. Data Lake is a new and increasingly popular way to store all of your data, structured and unstructured, in one, centralised repository. Since data can be stored as-is, there is no need to convert it to a predefined schema and you no longer need to know what questions you want to ask of your data beforehand.
In this webinar, you will discover how AWS gives you fast access to flexible and low-cost IT resources, so you can rapidly scale and build your data lake that can power any kind of analytics such as data warehousing, clickstream analytics, fraud detection, recommendation engines, event-driven ETL, serverless computing, and internet-of-things processing regardless of volume, velocity and variety of data.
Learning Objectives:
• Discover how you can rapidly scale and build your data lake with AWS.
• Explore the key pillars behind a successful data lake implementation.
• Learn how to use the Amazon Simple Storage Service (S3) as the basis for your data lake.
• Learn about the new AWS services recently launched, Amazon Athena and Amazon Redshift Spectrum, that help customers directly query that data lake.
Banking Circle: Money Laundering Beware: A Modern Approach to AML with Machin...Neo4j
by Ruben Menke, Lead Data Scientist at Banking Circle
In this talk, Banking Circle will show how a modern computational method is essential in the fight against money laundering.
Wonder what this data mesh stuff is all about? What are the principles of data mesh? Can you or should you consider data mesh as the approach for your analytics platform? And most important - how can Snowflake help?
Given in Montreal on 14-Dec-2021
DataOps - The Foundation for Your Agile Data ArchitectureDATAVERSITY
Achieving agility in data and analytics is hard. It’s no secret that most data organizations struggle to deliver the on-demand data products that their business customers demand. Recently, there has been much hype around new design patterns that promise to deliver this much sought-after agility.
In this webinar, Chris Bergh, CEO and Head Chef of DataKitchen will cut through the noise and describe several elegant and effective data architecture design patterns that deliver low errors, rapid development, and high levels of collaboration. He’ll cover:
• DataOps, Data Mesh, Functional Design, and Hub & Spoke design patterns;
• Where Data Fabric fits into your architecture;
• How different patterns can work together to maximize agility; and
• How a DataOps platform serves as the foundational superstructure for your agile architecture.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Accelerate your Cloud Migration Journey (Level 100)
Many enterprises have realized the benefits of migrating services to the cloud and are considering the next stage in their journey. In this webinar we will take you through the principles of cloud migration including the business benefits, cloud economics, methodologies and tools to accelerate your journey. We will also discuss the key enablers for cloud adoption based on real examples.
This is a Level 100 webinar
Speakers: Manav Prabhakar, Practice Manager, AWS Professional Services
Jon Austin, Principal Solutions Architect, Amazon Web Services
Parijat Mishra, Solutions Architect Manager, Amazon Web Services
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
How to Build the Data Mesh Foundation: A Principled Approach | Zhamak Dehghan...HostedbyConfluent
Organizations have been chasing the dream of data democratization, unlocking and accessing data at scale to serve their customers and business, for over a half a century from early days of data warehousing. They have been trying to reach this dream through multiple generations of architectures, such as data warehouse and data lake, through a cambrian explosion of tools and a large amount of investments to build their next data platform. Despite the intention and the investments the results have been middling.
In this keynote, Zhamak shares her observations on the failure modes of a centralized paradigm of a data lake, and its predecessor data warehouse.
She introduces Data Mesh, a paradigm shift in big data management that draws from modern distributed architecture: considering domains as the first class concern, applying self-sovereignty to distribute the ownership of data, applying platform thinking to create self-serve data infrastructure, and treating data as a product.
This talk introduces the principles underpinning data mesh and Zhamak's recent learnings in creating a path to bring data mesh to life in your organization.
From Insights to Action, How to build and maintain a Data Driven Organization...Amazon Web Services Korea
데이터는 혁신과 변혁의 토대입니다. 비즈니스 혁신을 이끄는 혁신은 특정 시점의 전략이나 솔루션이 아니라 성장을 위한 반복적이고 집단적인 계획입니다. 혁신에 이러한 접근 방식을 채택하는 기업은 전략과 비즈니스 문화에서 데이터를 기반으로 하는 경우가 많습니다. 이러한 접근 방식을 개발하려면 리더가 데이터를 조직의 자산처럼 취급하고 조직이 더 나은 비즈니스 성과를 위해 데이터를 활용할 수 있도록 권한을 부여해야 합니다. AWS와 Amazon이 어떻게 데이터와 분석을 활용하여 확장 가능한 비즈니스 효율성을 창출하고 고객의 가장 복잡한 문제를 해결하는 메커니즘을 개발했는지 알아보십시오.
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
The Analytics CoE: Positioning your Business Analytics Program for SuccessCartegraph
This Loras College Business Analytics Symposium breakout session presentation by Kiran Garimella, Ph.D., president and founder of XBITALIGN, explored the analytics center of excellence (CoE).
A business analytics program is more than the application of data science and Big Data technology to data. Success should be measured not only by the valuable insights the program delivers, but also by how well it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is not only from data to information, but also from information to knowledge, and from knowledge to intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence (CoE).
This describes a conceptual model approach to designing an enterprise data fabric. This is the set of hardware and software infrastructure, tools and facilities to implement, administer, manage and operate data operations across the entire span of the data within the enterprise across all data activities including data acquisition, transformation, storage, distribution, integration, replication, availability, security, protection, disaster recovery, presentation, analytics, preservation, retention, backup, retrieval, archival, recall, deletion, monitoring, capacity planning across all data storage platforms enabling use by applications to meet the data needs of the enterprise.
The conceptual data fabric model represents a rich picture of the enterprise’s data context. It embodies an idealised and target data view.
Designing a data fabric enables the enterprise respond to and take advantage of key related data trends:
• Internal and External Digital Expectations
• Cloud Offerings and Services
• Data Regulations
• Analytics Capabilities
It enables the IT function demonstrate positive data leadership. It shows the IT function is able and willing to respond to business data needs. It allows the enterprise to meet data challenges
• More and more data of many different types
• Increasingly distributed platform landscape
• Compliance and regulation
• Newer data technologies
• Shadow IT where the IT function cannot deliver IT change and new data facilities quickly
It is concerned with the design an open and flexible data fabric that improves the responsiveness of the IT function and reduces shadow IT.
Introduction to Snowflake Datawarehouse and Architecture for Big data company. Centralized data management. Snowpipe and Copy into a command for data loading. Stream loading and Batch Processing.
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.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Why an AI-Powered Data Catalog Tool is Critical to Business SuccessInformatica
Imagine a fast, more efficient business thriving on trusted data-driven decisions. An intelligent data catalog can help your organization discover, organize, and inventory all data assets across the org and democratize data with the right balance of governance and flexibility. Informatica's data catalog tools are powered by AI and can automate tedious data management tasks and offer immediate recommendations based on derived business intelligence. We offer data catalog workshops globally. Visit Informatica.com to attend one near you.
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
Master the Multi-Clustered Data Warehouse - SnowflakeMatillion
Snowflake is one of the most powerful, efficient data warehouses on the market today—and we joined forces with the Snowflake team to show you how it works!
In this webinar:
- Learn how to optimize Snowflake
- Hear insider tips and tricks on how to improve performance
- Get expert insights from Craig Collier, Technical Architect from Snowflake, and Kalyan Arangam, Solution Architect from Matillion
- Find out how leading brands like Converse, Duo Security, and Pets at Home use Snowflake and Matillion ETL to make data-driven decisions
- Discover how Matillion ETL and Snowflake work together to modernize your data world
- Learn how to utilize the impressive scalability of Snowflake and Matillion
Here we go! Our Experts take on Legacy Application Modernization with Microsoft Azure.
With Microsoft Azure gaining ground in the Cloud infrastructure race, this article aims to discuss the cutting-edge features and advantages of Legacy App Modernization using Microsoft Azure and the Key things to consider when your application takes on the Azure outfit. Article below derived from the White Paper presented by our MS Azure team. Read on to explore the top ways how Application Modernization using Microsoft Azure helps you gain the competitive edge.
Read more, please visit here: https://www.optisolbusiness.com/insight/legacy-application-modernization-with-microsoft-azure
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.
Enterprise Data Hub: The Next Big Thing in Big DataCloudera, Inc.
If you missed Strata + Hadoop World, you missed quite a bit. This year's event was packed with Big Data practitioners across industries who shared their experiences and how they are driving new innovations like never before. Just because you weren't there, doesn't mean you missed out.
In this session, we'll touch on a few of the key highlights from the show, including:
Key trends in Big Data adoption
The enterprise data hub
How the enterprise data hub is used in practice
DataOps - The Foundation for Your Agile Data ArchitectureDATAVERSITY
Achieving agility in data and analytics is hard. It’s no secret that most data organizations struggle to deliver the on-demand data products that their business customers demand. Recently, there has been much hype around new design patterns that promise to deliver this much sought-after agility.
In this webinar, Chris Bergh, CEO and Head Chef of DataKitchen will cut through the noise and describe several elegant and effective data architecture design patterns that deliver low errors, rapid development, and high levels of collaboration. He’ll cover:
• DataOps, Data Mesh, Functional Design, and Hub & Spoke design patterns;
• Where Data Fabric fits into your architecture;
• How different patterns can work together to maximize agility; and
• How a DataOps platform serves as the foundational superstructure for your agile architecture.
Data Lakehouse, Data Mesh, and Data Fabric (r1)James Serra
So many buzzwords of late: Data Lakehouse, Data Mesh, and Data Fabric. What do all these terms mean and how do they compare to a data warehouse? In this session I’ll cover all of them in detail and compare the pros and cons of each. I’ll include use cases so you can see what approach will work best for your big data needs.
Accelerate your Cloud Migration Journey (Level 100)
Many enterprises have realized the benefits of migrating services to the cloud and are considering the next stage in their journey. In this webinar we will take you through the principles of cloud migration including the business benefits, cloud economics, methodologies and tools to accelerate your journey. We will also discuss the key enablers for cloud adoption based on real examples.
This is a Level 100 webinar
Speakers: Manav Prabhakar, Practice Manager, AWS Professional Services
Jon Austin, Principal Solutions Architect, Amazon Web Services
Parijat Mishra, Solutions Architect Manager, Amazon Web Services
This is Part 4 of the GoldenGate series on Data Mesh - a series of webinars helping customers understand how to move off of old-fashioned monolithic data integration architecture and get ready for more agile, cost-effective, event-driven solutions. The Data Mesh is a kind of Data Fabric that emphasizes business-led data products running on event-driven streaming architectures, serverless, and microservices based platforms. These emerging solutions are essential for enterprises that run data-driven services on multi-cloud, multi-vendor ecosystems.
Join this session to get a fresh look at Data Mesh; we'll start with core architecture principles (vendor agnostic) and transition into detailed examples of how Oracle's GoldenGate platform is providing capabilities today. We will discuss essential technical characteristics of a Data Mesh solution, and the benefits that business owners can expect by moving IT in this direction. For more background on Data Mesh, Part 1, 2, and 3 are on the GoldenGate YouTube channel: https://www.youtube.com/playlist?list=PLbqmhpwYrlZJ-583p3KQGDAd6038i1ywe
Webinar Speaker: Jeff Pollock, VP Product (https://www.linkedin.com/in/jtpollock/)
Mr. Pollock is an expert technology leader for data platforms, big data, data integration and governance. Jeff has been CTO at California startups and a senior exec at Fortune 100 tech vendors. He is currently Oracle VP of Products and Cloud Services for Data Replication, Streaming Data and Database Migrations. While at IBM, he was head of all Information Integration, Replication and Governance products, and previously Jeff was an independent architect for US Defense Department, VP of Technology at Cerebra and CTO of Modulant – he has been engineering artificial intelligence based data platforms since 2001. As a business consultant, Mr. Pollock was a Head Architect at Ernst & Young’s Center for Technology Enablement. Jeff is also the author of “Semantic Web for Dummies” and "Adaptive Information,” a frequent keynote at industry conferences, author for books and industry journals, formerly a contributing member of W3C and OASIS, and an engineering instructor with UC Berkeley’s Extension for object-oriented systems, software development process and enterprise architecture.
How to Build the Data Mesh Foundation: A Principled Approach | Zhamak Dehghan...HostedbyConfluent
Organizations have been chasing the dream of data democratization, unlocking and accessing data at scale to serve their customers and business, for over a half a century from early days of data warehousing. They have been trying to reach this dream through multiple generations of architectures, such as data warehouse and data lake, through a cambrian explosion of tools and a large amount of investments to build their next data platform. Despite the intention and the investments the results have been middling.
In this keynote, Zhamak shares her observations on the failure modes of a centralized paradigm of a data lake, and its predecessor data warehouse.
She introduces Data Mesh, a paradigm shift in big data management that draws from modern distributed architecture: considering domains as the first class concern, applying self-sovereignty to distribute the ownership of data, applying platform thinking to create self-serve data infrastructure, and treating data as a product.
This talk introduces the principles underpinning data mesh and Zhamak's recent learnings in creating a path to bring data mesh to life in your organization.
From Insights to Action, How to build and maintain a Data Driven Organization...Amazon Web Services Korea
데이터는 혁신과 변혁의 토대입니다. 비즈니스 혁신을 이끄는 혁신은 특정 시점의 전략이나 솔루션이 아니라 성장을 위한 반복적이고 집단적인 계획입니다. 혁신에 이러한 접근 방식을 채택하는 기업은 전략과 비즈니스 문화에서 데이터를 기반으로 하는 경우가 많습니다. 이러한 접근 방식을 개발하려면 리더가 데이터를 조직의 자산처럼 취급하고 조직이 더 나은 비즈니스 성과를 위해 데이터를 활용할 수 있도록 권한을 부여해야 합니다. AWS와 Amazon이 어떻게 데이터와 분석을 활용하여 확장 가능한 비즈니스 효율성을 창출하고 고객의 가장 복잡한 문제를 해결하는 메커니즘을 개발했는지 알아보십시오.
The data lake has become extremely popular, but there is still confusion on how it should be used. In this presentation I will cover common big data architectures that use the data lake, the characteristics and benefits of a data lake, and how it works in conjunction with a relational data warehouse. Then I’ll go into details on using Azure Data Lake Store Gen2 as your data lake, and various typical use cases of the data lake. As a bonus I’ll talk about how to organize a data lake and discuss the various products that can be used in a modern data warehouse.
The Analytics CoE: Positioning your Business Analytics Program for SuccessCartegraph
This Loras College Business Analytics Symposium breakout session presentation by Kiran Garimella, Ph.D., president and founder of XBITALIGN, explored the analytics center of excellence (CoE).
A business analytics program is more than the application of data science and Big Data technology to data. Success should be measured not only by the valuable insights the program delivers, but also by how well it is sustained and how much the ‘analytics mindset’ becomes part of the company’s DNA. The journey is not only from data to information, but also from information to knowledge, and from knowledge to intelligence. The foundation for making this happen is a well-structured Analytics Center of Excellence (CoE).
This describes a conceptual model approach to designing an enterprise data fabric. This is the set of hardware and software infrastructure, tools and facilities to implement, administer, manage and operate data operations across the entire span of the data within the enterprise across all data activities including data acquisition, transformation, storage, distribution, integration, replication, availability, security, protection, disaster recovery, presentation, analytics, preservation, retention, backup, retrieval, archival, recall, deletion, monitoring, capacity planning across all data storage platforms enabling use by applications to meet the data needs of the enterprise.
The conceptual data fabric model represents a rich picture of the enterprise’s data context. It embodies an idealised and target data view.
Designing a data fabric enables the enterprise respond to and take advantage of key related data trends:
• Internal and External Digital Expectations
• Cloud Offerings and Services
• Data Regulations
• Analytics Capabilities
It enables the IT function demonstrate positive data leadership. It shows the IT function is able and willing to respond to business data needs. It allows the enterprise to meet data challenges
• More and more data of many different types
• Increasingly distributed platform landscape
• Compliance and regulation
• Newer data technologies
• Shadow IT where the IT function cannot deliver IT change and new data facilities quickly
It is concerned with the design an open and flexible data fabric that improves the responsiveness of the IT function and reduces shadow IT.
Introduction to Snowflake Datawarehouse and Architecture for Big data company. Centralized data management. Snowpipe and Copy into a command for data loading. Stream loading and Batch Processing.
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.
Data Catalog for Better Data Discovery and GovernanceDenodo
Watch full webinar here: https://buff.ly/2Vq9FR0
Data catalogs are en vogue answering critical data governance questions like “Where all does my data reside?” “What other entities are associated with my data?” “What are the definitions of the data fields?” and “Who accesses the data?” Data catalogs maintain the necessary business metadata to answer these questions and many more. But that’s not enough. For it to be useful, data catalogs need to deliver these answers to the business users right within the applications they use.
In this session, you will learn:
*How data catalogs enable enterprise-wide data governance regimes
*What key capability requirements should you expect in data catalogs
*How data virtualization combines dynamic data catalogs with delivery
Why an AI-Powered Data Catalog Tool is Critical to Business SuccessInformatica
Imagine a fast, more efficient business thriving on trusted data-driven decisions. An intelligent data catalog can help your organization discover, organize, and inventory all data assets across the org and democratize data with the right balance of governance and flexibility. Informatica's data catalog tools are powered by AI and can automate tedious data management tasks and offer immediate recommendations based on derived business intelligence. We offer data catalog workshops globally. Visit Informatica.com to attend one near you.
DataOps: An Agile Method for Data-Driven OrganizationsEllen Friedman
DataOps expands DevOps philosophy to include data-heavy roles (data engineering & data science). DataOps uses better cross-functional collaboration for flexibility, fast time to value and an agile workflow for data-intensive applications including machine learning pipelines. (Strata Data San Jose March 2018)
Master the Multi-Clustered Data Warehouse - SnowflakeMatillion
Snowflake is one of the most powerful, efficient data warehouses on the market today—and we joined forces with the Snowflake team to show you how it works!
In this webinar:
- Learn how to optimize Snowflake
- Hear insider tips and tricks on how to improve performance
- Get expert insights from Craig Collier, Technical Architect from Snowflake, and Kalyan Arangam, Solution Architect from Matillion
- Find out how leading brands like Converse, Duo Security, and Pets at Home use Snowflake and Matillion ETL to make data-driven decisions
- Discover how Matillion ETL and Snowflake work together to modernize your data world
- Learn how to utilize the impressive scalability of Snowflake and Matillion
Here we go! Our Experts take on Legacy Application Modernization with Microsoft Azure.
With Microsoft Azure gaining ground in the Cloud infrastructure race, this article aims to discuss the cutting-edge features and advantages of Legacy App Modernization using Microsoft Azure and the Key things to consider when your application takes on the Azure outfit. Article below derived from the White Paper presented by our MS Azure team. Read on to explore the top ways how Application Modernization using Microsoft Azure helps you gain the competitive edge.
Read more, please visit here: https://www.optisolbusiness.com/insight/legacy-application-modernization-with-microsoft-azure
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.
Enterprise Data Hub: The Next Big Thing in Big DataCloudera, Inc.
If you missed Strata + Hadoop World, you missed quite a bit. This year's event was packed with Big Data practitioners across industries who shared their experiences and how they are driving new innovations like never before. Just because you weren't there, doesn't mean you missed out.
In this session, we'll touch on a few of the key highlights from the show, including:
Key trends in Big Data adoption
The enterprise data hub
How the enterprise data hub is used in practice
Evolution from Apache Hadoop to the Enterprise Data Hub by Cloudera - ArabNet...ArabNet ME
A new foundation for the Modern Information Architecture.
Speaker: Amr Awadallah, CTO & Cofounder, Cloudera
Our legacy information architecture is not able to cope with the realities of today's business. This is because it is not able to scale to meet our SLAs due to separation of storage and compute, economically store the volumes and types of data we currently confront, provide the agility necessary for innovation, and most importantly, provide a full 360 degree view of our customers, products, and business. In this talk Dr. Amr Awadallah will present the Enterprise Data Hub (EDH) as the new foundation for the modern information architecture. Built with Apache Hadoop at the core, the EDH is an extremely scalable, flexible, and fault-tolerant, data processing system designed to put data at the center of your business.
Cloudera Federal Forum 2014: The Building Blocks of the Enterprise Data HubCloudera, Inc.
Chief Technologist, Office of the CTO at Cloudera Eli Collins, shares the story of the enterprise data hub and how it relates to the enterprise data warehouse.
Hadoop World 2011: How Hadoop Revolutionized Business Intelligence and Advanc...Cloudera, Inc.
"Amr Awadallah served as the VP of Engineering of Yahoo's Product
Intelligence Engineering (PIE) team for a number of years. The PIE
team was responsible for business intelligence and advanced data
analytics across a number of Yahoo's key consumer facing properties (search, mail, news, finance, sports, etc). Amr will share the data architecture that PIE had implementted before Hadoop was deployed and the headaches that architecture entailed. Amr will then show how most, if not all of these headaches were eliminated once Hadoop was deployed. Amr will illustrate how Hadoop and Relational Database complement each other within the traditional business intelligence data stack, and how that enables organizations to access all their data under different
operational and economic constraints."
This is a talk that I gave at Stanford's EE203 (Entrepreneurial Engineer) on Tuesday Feb 9th, 2010. It covers my experience at Stanford, VivaSmart, Yahoo, Accel Partners, and Cloudera.
Rethink Analytics with an Enterprise Data HubCloudera, Inc.
Have you run into one or more of the following barriers or limitations with your existing data warehousing architecture:
> Increasingly high data storage and/or processing costs?
> Silos of data sources?
> Complexity of management and security?
> Lack of analytics agility?
ElasticES-Hadoop: Bridging the world of Hadoop and ElasticsearchMapR Technologies
In this talk, we will provide an overview of Elasticsearch for Apache Hadoop (ES-Hadoop), which includes integrations between the various Hadoop libraries, whether batch (Map/Reduce, Pig, Hive) or stream oriented (such as Apache Spark). We will also cover the YARN support and the HDFS snapshot/restore plugin available as part of ES-Hadoop. We will talk about the upcoming ES-Hadoop 2.1 GA release and near-term roadmap.
Real-time Puppies and Ponies - Evolving Indicator Recommendations in Real-timeTed Dunning
This talk describes how indicator-based recommendations can be evolved in real time. Normally, indicator-based recommendations use a large off-line computation to understand the general structure of items to be recommended and then make recommendations in real-time to users based on a comparison of their recent history versus the large-scale product of the off-line computation.
In this talk, I show how the same components of the off-line computation that guarantee linear scalability in a batch setting also give strict real-time bounds on the cost of a practical real-time implementation of the indicator computation.
Data volumes have experienced explosive growth in recent years, and that data is being generated from sources that are increasingly complex and varied. Harnessing and refining value from this data requires a new approach as data extraction, transformation, and loading (ETL) becoming increasingly more costly and difficult to scale.
Organizations are looking to leverage Hadoop as an enterprise data hub—also called a “data lake” or “data reservoir”—as a key component of their data architecture to augment their data warehouse, ETL and analytical systems in order to maximize their existing investments, reduce costs, and unlock new business value from their data.
In this webinar, you will learn:
Real-world examples that illustrate why Hadoop is the best low-cost data hub, data lake, or data landing zone (staging area) option for ETL processing
Proof points that demonstrate advantages of Hadoop and its ability to scale to manage increasing data volumes and support exploratory big data analytics
Proven best practices for a cost-effective, reliable way to implement a data management platform for your entire big data analytical ecosystem
Hidden issues to be aware of in deploying your data hub/data lake
In this Strata+Hadoop World 2015 presentation, Ron Bodkin, President of Think Big, a Teradata company, explains changes for data modeling on big data systems and five important new analytic patterns becoming more commonplace as companies grow their data driven capabilities.
Sumo Logic Webinar: Visibility into your Host MetricsSumo Logic
Webinar: https://youtu.be/WOeR_ukK01A
This webinar walks users on how to install/upgrade a Collector to start ingesting host metrics, query them and add their charts into dashboards.
See how to take advantage of our out-of-the-box content in our Apps, and hear about Cloudwatch and Graphite sources for metrics.
Get started with your Host Metrics!
QuickStart your Sumo Logic service with this exclusive webinar. At these monthly live events you will learn how to capitalize on critical capabilities that can amplify your log analytics and monitoring experience while providing you with meaningful business and IT insights.
MongoDB IoT City Tour STUTTGART: Hadoop and future data management. By, ClouderaMongoDB
Bernard Doering, Senior Slaes Director DACH, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
Manufacturers have an abundance of data, whether from connected sensors, plant systems, manufacturing systems, claims systems and external data from industry and government. Manufacturers face increased challenges from continually improving product quality, reducing warranty and recall costs to efficiently leveraging their supply chain. For example, giving the manufacturer a complete view of the product and customer information integrating manufacturing and plant floor data, with as built product configurations with sensor data from customer use to efficiently analyze warranty claim information to reduce detection to correction time, detect fraud and even become proactive around issues requires a capable enterprise data hub that integrates large volumes of both structured and unstructured information. Learn how an enterprise data hub built on Hadoop provides the tools to support analysis at every level in the manufacturing organization.
MongoDB IoT City Tour LONDON: Hadoop and the future of data management. By, M...MongoDB
Mark Lewis, Senior MArketing Director EMEA, Cloudera.
Hadoop and the Future of Data Management. As Hadoop takes the data management market by storm, organisations are evolving the role it plays in the modern data centre. Explore how this disruptive technology is quickly transforming an industry and how you can leverage it today, in combination with MongoDB, to drive meaningful change in your business.
Simplifying Real-Time Architectures for IoT with Apache KuduCloudera, Inc.
3 Things to Learn About:
*Building scalable real time architectures for managing data from IoT
*Processing data in real time with components such as Kudu & Spark
*Customer case studies highlighting real-time IoT use cases
Intel and Cloudera: Accelerating Enterprise Big Data SuccessCloudera, Inc.
The data center has gone through several inflection points in the past decades: adoption of Linux, migration from physical infrastructure to virtualization and Cloud, and now large-scale data analytics with Big Data and Hadoop.
Please join us to learn about how Cloudera and Intel are jointly innovating through open source software to enable Hadoop to run best on IA (Intel Architecture) and to foster the evolution of a vibrant Big Data ecosystem.
Oracle Big Data Appliance and Big Data SQL for advanced analyticsjdijcks
Overview presentation showing Oracle Big Data Appliance and Oracle Big Data SQL in combination with why this really matters. Big Data SQL brings you the unique ability to analyze data across the entire spectrum of system, NoSQL, Hadoop and Oracle Database.
This talk was held at the 13th meeting on Sept 23rd 2014 by Bruno Ungermann.
Conceptual overview of Hadoop based analytics, comparison between data warehouse architecture and Big Data architecture, characteristics of „schema on read“, typical Big Data use cases like customer analytics, operational analytics and EDW optimization, short software demo
Nov 2014 talk to SW Data Meetup by Mike Olson, co-founder and chairman of Cloudera.
In business, we often deal with hype around trends in society, politics, economy and technology. We know we need to take claims of the next big thing with a grain of salt and that we should be careful not to set expectations too high. However, with Big Data analytics, the opposite is true. The hype that accompanies it actually conceals the enormity of its impact on the way we do business. In this talk I’ll discuss how new 'Data Driven' economies are emerging through relentless innovation across the public and private sectors.
Mike (co-founded Cloudera in 2008 and served as its CEO until 2013 when he took on his current role of chief strategy officer (CSO.) As CSO, Mike is responsible for Cloudera’s product strategy, open source leadership, engineering alignment and direct engagement with customers. Prior to Cloudera Mike was CEO of Sleepycat Software, makers of Berkeley DB, the open source embedded database engine. Mike spent two years at Oracle Corporation as vice president for Embedded Technologies after Oracle’s acquisition of Sleepycat in 2006. Prior to joining Sleepycat, Mike held technical and business positions at database vendors Britton Lee, Illustra Information Technologies and Informix Software. Mike has a Bachelor’s and a Master’s Degree in Computer Science from the University of California, Berkeley.
Turning Data into Business Value with a Modern Data PlatformCloudera, Inc.
3 Things to Learn About:
-Real-time analytics and data in motion
-Self-service access for SQL analysts and data scientists alike
-Public cloud and hybrid infrastructure
Cloudera Federal Forum 2014: Hadoop's Impact on the Future of Data ManagementCloudera, Inc.
Chief Strategy Officer, Chairman and Founder of Cloudera Mike Olson, shares thoughts on the future of data management and how it relates to the public sector.
Syncsort, Tableau, & Cloudera present: Break the Barriers to Big Data InsightCloudera, Inc.
Rethink data management and learn how to break down barriers to Big Data insight with Cloudera's enterprise data hub (EDH), Syncsort offload solutions, and Tableau Software visualization and analytics.
Hadoop in 2015: Keys to Achieving Operational Excellence for the Real-Time En...MapR Technologies
In this webinar, Carl W. Olofson, Research Vice President, Application Development and Deployment for IDC, and Dale Kim, Director of Industry Solutions for MapR, will provide an insightful outlook for Hadoop in 2015, and will outline why enterprises should consider using Hadoop as a "Decision Data Platform" and how it can function as a single platform for both online transaction processing (OLTP) and real-time analytics.
Turning Petabytes of Data into Profit with Hadoop for the World’s Biggest Ret...Cloudera, Inc.
PRGX is the world's leading provider of accounts payable audit services and works with leading global retailers. As new forms of data started to flow into their organizations, standard RDBMS systems were not allowing them to scale. Now, by using Talend with Cloudera Enterprise, they are able to acheive a 9-10x performance benefit in processing data, reduce errors, and now provide more innovative products and services to end customers.
Watch this webinar to learn how PRGX worked with Cloudera and Talend to create a high-performance computing platform for data analytics and discovery that rapidly allows them to process, model, and serve massive amount of structured and unstructured data.
Building a Modern Analytic Database with Cloudera 5.8Cloudera, Inc.
Analytic workloads and the ability to determine “what happened” are some of the most common use cases across enterprises today - helping you understand and adapt based on changing trends. However, for most businesses today, they are only able to see a piece of the story. Analytics are limited by the amount of data able to be stored and ultimately accessed, it’s time-intensive to bring in new datasets or fit unstructured data into rigid schemas, and user access is constrained to a select few who must already know the questions they’re trying to answer.
It’s no surprise that big data is disrupting this modus operandi for analytics. A modern, Hadoop-based platform is designed to help businesses break free of these analytic limitations, providing a new kind of adaptive, high-performance analytic database. The recent release of Cloudera 5.8 continues to advance Cloudera Enterprise as the foundation for these analytic workloads.
Join Justin Erickson, Senior Director of Product Management at Cloudera, and Andy Frey, Chief Technology Officer at Marketing Associates, as they discuss:
-What technology is needed to build a modern analytic database with Hadoop
-What’s new with Cloudera 5.8
-How to align your teams around agile analytics
-Real world success from Marketing Associates
-What’s next for Cloudera Enterprise’s Analytic Database
Keynote from Big Data World Show Singapore, April 2015.
• How is data driving change?
• Where are the opportunities, across industries?
• What is required to gain value from data?
• How can you get started today?
The Cloudera Impala project is pioneering the next generation of Hadoop capabilities: the convergence of interactive SQL queries with the capacity, scalability, and flexibility of a Hadoop cluster. In this webinar, join Cloudera and MicroStrategy to learn how Impala works, how it is uniquely architected to provide an interactive SQL experience native to Hadoop, and how you can leverage the power of MicroStrategy 9.3.1 to easily tap into more data and make new discoveries.
Complement Your Existing Data Warehouse with Big Data & HadoopDatameer
To view the full webinar, please go to: http://info.datameer.com/Slideshare-Complement-Your-Existing-EDW-with-Hadoop-OnDemand.html
With 40% yearly growth in data volumes, traditional data warehouses have become increasingly expensive and challenging.
Much of today’s new data sources are unstructured, making the structured data warehouse an unsuitable platform for analyses. As a result, organizations now look at Hadoop as a data platform to complement existing BI data warehouses, and a scalable, flexible and cost-effective solution for data storage and analysis.
Join Datameer and Cloudera in this webinar to discuss how Hadoop and big data analytics can help to:
-Get all the data your business needs quickly into one environment
Shorten the time to insight from months to days
Extend the life of your existing data warehouse investments
Enable your business analysts to ask and answer bigger questions
Similar to The Future of Data Management: The Enterprise Data Hub (20)
Cloudera Data Impact Awards 2021 - Finalists Cloudera, Inc.
This annual program recognizes organizations who are moving swiftly towards the future and building innovative solutions by making what was impossible yesterday, possible today.
The winning organizations' implementations demonstrate outstanding achievements in fulfilling their mission, technical advancement, and overall impact.
The 2021 Data Impact Awards recognize organizations' achievements with the Cloudera Data Platform in seven categories:
Data Lifecycle Connection
Data for Enterprise AI
Cloud Innovation
Security & Governance Leadership
People First
Data for Good
Industry Transformation
2020 Cloudera Data Impact Awards FinalistsCloudera, Inc.
Cloudera is proud to present the 2020 Data Impact Awards Finalists. This annual program recognizes organizations running the Cloudera platform for the applications they've built and the impact their data projects have on their organizations, their industries, and the world. Nominations were evaluated by a panel of independent thought-leaders and expert industry analysts, who then selected the finalists and winners. Winners exemplify the most-cutting edge data projects and represent innovation and leadership in their respective industries.
Machine Learning with Limited Labeled Data 4/3/19Cloudera, Inc.
Cloudera Fast Forward Labs’ latest research report and prototype explore learning with limited labeled data. This capability relaxes the stringent labeled data requirement in supervised machine learning and opens up new product possibilities. It is industry invariant, addresses the labeling pain point and enables applications to be built faster and more efficiently.
Data Driven With the Cloudera Modern Data Warehouse 3.19.19Cloudera, Inc.
In this session, we will cover how to move beyond structured, curated reports based on known questions on known data, to an ad-hoc exploration of all data to optimize business processes and into the unknown questions on unknown data, where machine learning and statistically motivated predictive analytics are shaping business strategy.
Introducing Cloudera DataFlow (CDF) 2.13.19Cloudera, Inc.
Watch this webinar to understand how Hortonworks DataFlow (HDF) has evolved into the new Cloudera DataFlow (CDF). Learn about key capabilities that CDF delivers such as -
-Powerful data ingestion powered by Apache NiFi
-Edge data collection by Apache MiNiFi
-IoT-scale streaming data processing with Apache Kafka
-Enterprise services to offer unified security and governance from edge-to-enterprise
Introducing Cloudera Data Science Workbench for HDP 2.12.19Cloudera, Inc.
Cloudera’s Data Science Workbench (CDSW) is available for Hortonworks Data Platform (HDP) clusters for secure, collaborative data science at scale. During this webinar, we provide an introductory tour of CDSW and a demonstration of a machine learning workflow using CDSW on HDP.
Shortening the Sales Cycle with a Modern Data Warehouse 1.30.19Cloudera, Inc.
Join Cloudera as we outline how we use Cloudera technology to strengthen sales engagement, minimize marketing waste, and empower line of business leaders to drive successful outcomes.
Leveraging the cloud for analytics and machine learning 1.29.19Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on Azure. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Modernizing the Legacy Data Warehouse – What, Why, and How 1.23.19Cloudera, Inc.
Join us to learn about the challenges of legacy data warehousing, the goals of modern data warehousing, and the design patterns and frameworks that help to accelerate modernization efforts.
Leveraging the Cloud for Big Data Analytics 12.11.18Cloudera, Inc.
Learn how organizations are deriving unique customer insights, improving product and services efficiency, and reducing business risk with a modern big data architecture powered by Cloudera on AWS. In this webinar, you see how fast and easy it is to deploy a modern data management platform—in your cloud, on your terms.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Explore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Extending Cloudera SDX beyond the PlatformCloudera, Inc.
Cloudera SDX is by no means no restricted to just the platform; it extends well beyond. In this webinar, we show you how Bardess Group’s Zero2Hero solution leverages the shared data experience to coordinate Cloudera, Trifacta, and Qlik to deliver complete customer insight.
Federated Learning: ML with Privacy on the Edge 11.15.18Cloudera, Inc.
Join Cloudera Fast Forward Labs Research Engineer, Mike Lee Williams, to hear about their latest research report and prototype on Federated Learning. Learn more about what it is, when it’s applicable, how it works, and the current landscape of tools and libraries.
Analyst Webinar: Doing a 180 on Customer 360Cloudera, Inc.
451 Research Analyst Sheryl Kingstone, and Cloudera’s Steve Totman recently discussed how a growing number of organizations are replacing legacy Customer 360 systems with Customer Insights Platforms.
Build a modern platform for anti-money laundering 9.19.18Cloudera, Inc.
In this webinar, you will learn how Cloudera and BAH riskCanvas can help you build a modern AML platform that reduces false positive rates, investigation costs, technology sprawl, and regulatory risk.
Introducing the data science sandbox as a service 8.30.18Cloudera, Inc.
How can companies integrate data science into their businesses more effectively? Watch this recorded webinar and demonstration to hear more about operationalizing data science with Cloudera Data Science Workbench on Cazena’s fully-managed cloud platform.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
The Art of the Pitch: WordPress Relationships and SalesLaura Byrne
Clients don’t know what they don’t know. What web solutions are right for them? How does WordPress come into the picture? How do you make sure you understand scope and timeline? What do you do if sometime changes?
All these questions and more will be explored as we talk about matching clients’ needs with what your agency offers without pulling teeth or pulling your hair out. Practical tips, and strategies for successful relationship building that leads to closing the deal.
Software Delivery At the Speed of AI: Inflectra Invests In AI-Powered QualityInflectra
In this insightful webinar, Inflectra explores how artificial intelligence (AI) is transforming software development and testing. Discover how AI-powered tools are revolutionizing every stage of the software development lifecycle (SDLC), from design and prototyping to testing, deployment, and monitoring.
Learn about:
• The Future of Testing: How AI is shifting testing towards verification, analysis, and higher-level skills, while reducing repetitive tasks.
• Test Automation: How AI-powered test case generation, optimization, and self-healing tests are making testing more efficient and effective.
• Visual Testing: Explore the emerging capabilities of AI in visual testing and how it's set to revolutionize UI verification.
• Inflectra's AI Solutions: See demonstrations of Inflectra's cutting-edge AI tools like the ChatGPT plugin and Azure Open AI platform, designed to streamline your testing process.
Whether you're a developer, tester, or QA professional, this webinar will give you valuable insights into how AI is shaping the future of software delivery.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
6. Customer Success Across Industries
Financial &
Business Services
Telecom &
Technology
Healthcare &
Life Sciences
Media &
Information
Retail &
Consumer
Energy &
Public Sector
Cloudera has built and maintains the industry’s most extensive partner ecosystem to ensure that our customers can leverage their existing investments in tools and skills as they adopt new Hadoop technology. Our goal is to help you minimize disruption while delivering maximum value.
Over 800 partners across hardware, software and services – including the leaders in all major market segments
Continue to leverage the technologies and solution providers you’ve already invested in
Drive additional value through integrated solutions
Alright, we have a partner we’d like to now bring up to the stage. It is with great pleasure that I introduce Sanjay Gojija from Intel to give you some insight on Accelerating Enterprise Big Data Success!