Self-service analytics tools solved one problem but created another. Now we need data catalogs and self-service data.
When you're done reading the slides, you can download our research: The Ultimate Guide to Data Catalogs https://www.eckerson.com/articles/the-ultimate-guide-to-data-catalogs-key-things-to-consider-when-selecting-a-data-catalog
We also help you choose a data catalog and teach you how to implement it across your enterprise. Contact us-https://www.eckerson.com/consulting
Learn about the organizational and architectural strategies needed to make self-service analytics successful. Self-service is more about process and training instead of only focusing on tools.
Download this research to read about self-service architecture in detail:https://www.eckerson.com/articles/a-reference-architecture-for-self-service-analytics
If you need help with self-service analytics, data architecture or data management, contact us on the following link: https://www.eckerson.com/consulting
Metadata Mastery: A Big Step for BI ModernizationEric Kavanagh
Modernizing data management is on everyone’s mind today. Making the shift from data management practices of the BI era to modern data management is essential but it is also challenging. Whether you’re updating the back end by migrating your data warehouses to the cloud or advancing the front end with a shift from legacy BI tools to self-service analysis and visualization, it is critical to know the data that you have and to understand data lineage. Data inventory, data glossary, and data lineage are all metadata dependent. But legacy BI metadata is typically proprietary, non-integrated, and collected inconsistently by a variety of disparate tools. The metadata muddle is a serious inhibitor to modernization efforts. Metadata consolidation and centralization are the keys to overcoming this barrier. What if all this were automated?
Join us to learn:
- How a smart and innovative new technology resolves metadata disparity
- How metadata management automation accelerates modernization efforts
- How metadata management automation reduces errors and improves quality of results from data management modernization projects
- How metadata management automation and data cataloging work together to help you move rapidly to the next generation of BI and analytics
This presentation will discuss the stories of 3 companies that span different industries; what challenges they faced and how cloud analytics solved for them; what technologies were implemented to solve the challenges; and how they were able to benefit from their new cloud analytics environments.
The objectives of this session include:
• Detail and explain the key benefits and advantages of moving BI and analytics workloads to the cloud, and why companies shouldn’t wait any longer to make their move.
• Compare the different analytics cloud options companies have, and the pros and cons of each.
• Describe some of the challenges companies may face when moving their analytics to the cloud, and what they need to prepare for.
• Provide the case studies of three companies, what issues they were solving for, what technologies they implemented and why, and how they benefited from their new solutions.
• Learn what to look for one considering a partner and trusted advisor to assist with an analytics cloud migration.
Slides: Success Stories for Data-to-CloudDATAVERSITY
Companies are finding accessing data from a variety of sources can be labor-intensive and costly. Oftentimes these companies are looking to cloud solutions, but are then finding the traditional architecture brittle when trying to move data to the cloud, which can drain organizations of time and resources.
Join this webinar to hear several company success stories, the data-to-cloud issues they were encountering, and the steps these companies took to bring their cloud architecture to a successful, real-time analytic solution unlocking massive amounts of fresh enterprise-wide on a continuous basis.
In addition, you will learn how to:
• Modernize the ETL process to one that’s fast, flexible, and scalable
• Supply users with up-to-date, accurate, trusted data
• Increase your time to value with data in the cloud
• Best practices on how to minimize resource overhead
ADV Slides: Building and Growing Organizational Analytics with Data LakesDATAVERSITY
Data lakes are providing immense value to organizations embracing data science.
In this webinar, William will discuss the value of having broad, detailed, and seemingly obscure data available in cloud storage for purposes of expanding Data Science in the organization.
Do-It-Yourself (DIY) Data Governance FrameworkDATAVERSITY
A worthwhile Data Governance framework includes the core component of a successful program as viewed by the different levels of the organization. Each of the components is addressed at each of the levels, providing insight into key ideas and terminology used to attract participation across the organization. A framework plays a key role in setting up and sustaining a Data Governance program.
In this RWDG webinar, Bob Seiner will share two frameworks. The first is a basic cross-reference of components and levels, while the second can be used to compare and contrast different approaches to implementing Data Governance. When this webinar is finished, you will be able to customize the frameworks to outline the most appropriate manner for you to improve your likelihood of DG success.
In this webinar, Bob will discuss and share:
- Customizing a framework to match organizational requirements
- The core components and levels of an industry framework
- How to complete a Data Governance framework
- Using the framework to enable DG program success
- Measuring value through the DIY DG framework
Learn about the organizational and architectural strategies needed to make self-service analytics successful. Self-service is more about process and training instead of only focusing on tools.
Download this research to read about self-service architecture in detail:https://www.eckerson.com/articles/a-reference-architecture-for-self-service-analytics
If you need help with self-service analytics, data architecture or data management, contact us on the following link: https://www.eckerson.com/consulting
Metadata Mastery: A Big Step for BI ModernizationEric Kavanagh
Modernizing data management is on everyone’s mind today. Making the shift from data management practices of the BI era to modern data management is essential but it is also challenging. Whether you’re updating the back end by migrating your data warehouses to the cloud or advancing the front end with a shift from legacy BI tools to self-service analysis and visualization, it is critical to know the data that you have and to understand data lineage. Data inventory, data glossary, and data lineage are all metadata dependent. But legacy BI metadata is typically proprietary, non-integrated, and collected inconsistently by a variety of disparate tools. The metadata muddle is a serious inhibitor to modernization efforts. Metadata consolidation and centralization are the keys to overcoming this barrier. What if all this were automated?
Join us to learn:
- How a smart and innovative new technology resolves metadata disparity
- How metadata management automation accelerates modernization efforts
- How metadata management automation reduces errors and improves quality of results from data management modernization projects
- How metadata management automation and data cataloging work together to help you move rapidly to the next generation of BI and analytics
This presentation will discuss the stories of 3 companies that span different industries; what challenges they faced and how cloud analytics solved for them; what technologies were implemented to solve the challenges; and how they were able to benefit from their new cloud analytics environments.
The objectives of this session include:
• Detail and explain the key benefits and advantages of moving BI and analytics workloads to the cloud, and why companies shouldn’t wait any longer to make their move.
• Compare the different analytics cloud options companies have, and the pros and cons of each.
• Describe some of the challenges companies may face when moving their analytics to the cloud, and what they need to prepare for.
• Provide the case studies of three companies, what issues they were solving for, what technologies they implemented and why, and how they benefited from their new solutions.
• Learn what to look for one considering a partner and trusted advisor to assist with an analytics cloud migration.
Slides: Success Stories for Data-to-CloudDATAVERSITY
Companies are finding accessing data from a variety of sources can be labor-intensive and costly. Oftentimes these companies are looking to cloud solutions, but are then finding the traditional architecture brittle when trying to move data to the cloud, which can drain organizations of time and resources.
Join this webinar to hear several company success stories, the data-to-cloud issues they were encountering, and the steps these companies took to bring their cloud architecture to a successful, real-time analytic solution unlocking massive amounts of fresh enterprise-wide on a continuous basis.
In addition, you will learn how to:
• Modernize the ETL process to one that’s fast, flexible, and scalable
• Supply users with up-to-date, accurate, trusted data
• Increase your time to value with data in the cloud
• Best practices on how to minimize resource overhead
ADV Slides: Building and Growing Organizational Analytics with Data LakesDATAVERSITY
Data lakes are providing immense value to organizations embracing data science.
In this webinar, William will discuss the value of having broad, detailed, and seemingly obscure data available in cloud storage for purposes of expanding Data Science in the organization.
Do-It-Yourself (DIY) Data Governance FrameworkDATAVERSITY
A worthwhile Data Governance framework includes the core component of a successful program as viewed by the different levels of the organization. Each of the components is addressed at each of the levels, providing insight into key ideas and terminology used to attract participation across the organization. A framework plays a key role in setting up and sustaining a Data Governance program.
In this RWDG webinar, Bob Seiner will share two frameworks. The first is a basic cross-reference of components and levels, while the second can be used to compare and contrast different approaches to implementing Data Governance. When this webinar is finished, you will be able to customize the frameworks to outline the most appropriate manner for you to improve your likelihood of DG success.
In this webinar, Bob will discuss and share:
- Customizing a framework to match organizational requirements
- The core components and levels of an industry framework
- How to complete a Data Governance framework
- Using the framework to enable DG program success
- Measuring value through the DIY DG framework
The Future of Data Warehousing and Data IntegrationEric Kavanagh
The rise of big data, data lakes and the cloud, coupled with increasingly stringent enterprise requirements, are reinventing the role of data warehousing in modern analytics ecosystems. The emerging generation of data warehouses is more flexible, agile and cloud-based than their predecessors, with a strong need for automation and real-time data integration.
Join this live webinar to learn:
-Typical requirements for data integration
-Common use cases and architectural patterns
-Guidelines and best practices to address data requirements
-Guidelines and best practices to apply architectural patterns
RWDG Slides: Governing Your Data Catalog, Business Glossary, and Data DictionaryDATAVERSITY
Data catalogs, business glossaries, and data dictionaries house the metadata that builds organizational confidence in your data. First and foremost, the people in your organization need to be engaged in leveraging the tools, understanding the data that is available and who is responsible for the data, and knowing how to get their hands on the data they need to perform their job function. This metadata will not govern itself.
Join Bob Seiner for the April RWDG webinar, where he will discuss how to govern the metadata in a data catalog, business glossary, and data dictionary. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must be governed. Learn how to govern that metadata in this webinar.
Bob will discuss the following subjects in this webinar:
• Successful Data Governance relies on value from very important tools
• What it means to govern your data catalog, business glossary, and data dictionary
• Why governing the metadata in these tools is so important
• The roles necessary to govern these tools
• Value expected from governing the catalog, glossary, and dictionary
The Ultimate Guide To Embedded Analytics Poojitha B
Did you know that the lack of in-context data prevents you from making smarter business decisions - and as a result, missing out on key revenue opportunities?
LoQutus helps organisations to innovate with analytics and to get insights with data visualisation. We also build large scale data layers to enable interaction with core data, and develop data-driven applications to deliver the insights our customers need. During this session we’ll share what we have learned along the way. We’ll show you our framework for self-service analytics & insights, and some successful case studies.
RWDG Slides: Using Tools to Advance Your Data Governance ProgramDATAVERSITY
Data Governance tools can be used to advance your Data Governance program … or they can become the reason why Data Governance fails to meet people’s expectations. Tools can be developed internally or acquired from reliable vendors to attempt to address your organization’s needs. Sometimes the best environment is made up of a hybrid of tools developed internally and tools acquired.
Join Bob Seiner for this month’s RWDG webinar where he will share tools that you can build yourself and talk about how the tools can be used to determine requirements to acquire outside tools. Tools developed internally at little or no cost have helped to solve many Data Governance problems. Several of these problems and their solutions will be described in detail during this webinar.
In this webinar, Bob will discuss:
• Several easy-to-build Data Governance tools
• Customizing these tools to address specific issues
• How internally developed tools can lead to tool acquisition
• Knowing when it is time to acquire tools
• Integrating DIY tools with acquired tools
7 steps for guides how to build a successful data strategyshopiawilson
Enterprise Data Strategy decisions and sets of choices that together, chart a high-level course of action to get high-level goals. Some important steps to build a successful data strategy.
Data Centric Development: Supercharge your web & mobile application developmentBright North
Many businesses are finding that their web and mobile applications aren’t providing the long-term solution they were hoping for. As consumers provide more and more useful data, these digital platforms don’t allow businesses to take advantage of the huge opportunities that data presents.
Our new whitepaper details the practical steps you can take to supercharge your web and mobile application development and stay ahead of the data revolution.
Slides: The Automated Business GlossaryDATAVERSITY
You can’t do business without being able to successfully extract insights from your organization’s data supply chain. You need a strong foundation for visibility and control of data. Flying by the seat of your pants, when it comes to analyzing your market, your performance, and your competitors’ performances, just doesn’t work.
In this webinar, we’ll examine the real-life daily struggles and frustrations plaguing the data supply chain and discuss how these struggles can be eliminated by automation of metadata operations such as data lineage, data discovery and business glossary.
When you attend this webinar, you will learn about:
• What data consumers are really spending their time on and why they are so frustrated
• The challenges of building a business glossary
• How to get started with an automated business glossary and why it’s critical for BI intelligence
Data Exploration and Analytics for the Modern BusinessDATAVERSITY
Every day, your business generates enormous quantities of data. How can you unlock its value? How can you build self-service exploration experiences that empower frontline decision-makers?
This webinar features Greg Jones from Smartling and Scott Hoover from Looker. Smartling is a powerful software platform for managing translation and localization of digital content. Looker is a data exploration platform that operates in the database. Together, Greg and Scott will introduce you to a modern approach to managing analytics in today’s fast-growing, web-centric business environments.
DataOps: Nine steps to transform your data science impact Strata London May 18Harvinder Atwal
According to Forrester Research, only 22% of companies are currently seeing a significant return from data science expenditures. Most data science implementations are high-cost IT projects, local applications that are not built to scale for production workflows, or laptop decision support projects that never impact customers. Despite this high failure rate, we keep hearing the same mantra and solutions over and over again. Everybody talks about how to create models, but not many people talk about getting them into production where they can impact customers.
Harvinder Atwal offers an entertaining and practical introduction to DataOps, a new and independent approach to delivering data science value at scale, used at companies like Facebook, Uber, LinkedIn, Twitter, and eBay. The key to adding value through DataOps is to adapt and borrow principles from Agile, Lean, and DevOps. However, DataOps is not just about shipping working machine learning models; it starts with better alignment of data science with the rest of the organization and its goals. Harvinder shares experience-based solutions for increasing your velocity of value creation, including Agile prioritization and collaboration, new operational processes for an end-to-end data lifecycle, developer principles for data scientists, cloud solution architectures to reduce data friction, self-service tools giving data scientists freedom from bottlenecks, and more. The DataOps methodology will enable you to eliminate daily barriers, putting your data scientists in control of delivering ever-faster cutting-edge innovation for your organization and customers.
ADV Slides: Increasing Artificial Intelligence Success with Master Data Manag...DATAVERSITY
Companies all over the world are going through a digital transformation now, which in many cases, is all about maturing the data environment and the use of data. Master data is key to this effort. All transformative projects require master data and usually many subject areas. Current efforts to deliver master data to the enterprise are cumbersome, inefficient, and met with limited acceptance.
We’ll look at enterprise use cases of artificial intelligence and show the master data that is needed. We’ll see what some MDM vendors are doing with AI and how the future of MDM will be shaped by looking at some specific MDM actions influenced by AI.
Introduction to Segment, Analytics API and Customer Data Platform. (Demo: Segment, AWS Redshift, Redash, Segment and GTM Alternatives) (Frontend Fighters Edition)
Recommended links:
https://segment.com/ - Analytics API and Customer Data Platform
https://open.segment.com/ - Open Source Projects of Segment
https://segment.com/docs/ - Documentation of Segment
https://redash.io/ - Open Sorce Data Dashboard
https://aws.amazon.com/redshift/ - Data Warehouse Solution
https://quicksight.aws/ - Business Analytics Service
https://www.ghostery.com/ - Tracker Detector
Keywords: business agility, tag managers, data-driven
Usually, DataOps means applying DevOps principles to existing data analytics projects. We accidentally reversed it, taking a DevOps initiative and catalyzing adoption of data-driven practices across our company.
What started as a practical initiative to bring better reliability and visibility to our software product had the unexpected effect of catalyzing a transformation that helped our organization become more data-driven across the company. What we learned in the process was how and why DevOps principles can naturally expand the role of a traditional operations team and bring wider culture change to the organization.
ADV Slides: Comparing the Enterprise Analytic SolutionsDATAVERSITY
Data is the foundation of any meaningful corporate initiative. Fully master the necessary data, and you’re more than halfway to success. That’s why leverageable (i.e., multiple use) artifacts of the enterprise data environment are so critical to enterprise success.
Build them once (keep them updated), and use again many, many times for many and diverse ends. The data warehouse remains focused strongly on this goal. And that may be why, nearly 40 years after the first database was labeled a “data warehouse,” analytic database products still target the data warehouse.
Advance Data Visualization and Storytelling Virtual WorkshopCCG
Join CCG and Microsoft for a virtual workshop, hosted by Senior BI Architect, Martin Rivera, taking you through a journey of advanced data visualization and storytelling.
Virtual Governance in a Time of Crisis WorkshopCCG
The CCGDG framework is focused on the following 5 key competencies. These 5 competencies were identified as areas within DG that have the biggest ROI for you, our customer. The pandemic has uncovered many challenges related to governance, therefore the backbone of this model is the emphasis on risk mitigation.
1. Program Management
2. Data Quality
3. Data Architecture
4. Metadata Management
5. Privacy
As digital channels continue to grow, they drive greater diversity in our data landscape. At Yorkshire Building Society, our purpose is to provide real help with real life and this relies on data from a myriad of sources. This diversity creates a need for points of intersection, where data can unite to feed customer and business insights. How do we create these hubs of intersection and what can modern technology offer?
Speaker:
Mark Walters
Lead Enterprise Data Architect for Data & Information
Yorkshire Building Society
This on-demand webinar will explore the challenges of working with legacy data and explain the technologies required to make that data a first-class citizen in modern cloud data environments while ensuring your costs don’t impact your business.
In this webinar viewers will understand:
- Challenges in integrating legacy systems with modern cloud data platforms
- Strategies for integrating legacy systems into a cloud architecture
- How Precisely Connect is helping customers to minimize costs while taking a modern approach to data integration
Bridging Legacy Systems and Cloud Data Platforms to Unlock Valuable Enterpris...Precisely
In this webinar users will understand:
- The benefits of data integration for driving business insights
- Challenges in integrating legacy systems with modern cloud data platforms
- Strategies for integrating legacy systems into a cloud architecture
- Benefits of real-time data replication with change data capture (CDC)
- How to future proof your data architecture
The Future of Data Warehousing and Data IntegrationEric Kavanagh
The rise of big data, data lakes and the cloud, coupled with increasingly stringent enterprise requirements, are reinventing the role of data warehousing in modern analytics ecosystems. The emerging generation of data warehouses is more flexible, agile and cloud-based than their predecessors, with a strong need for automation and real-time data integration.
Join this live webinar to learn:
-Typical requirements for data integration
-Common use cases and architectural patterns
-Guidelines and best practices to address data requirements
-Guidelines and best practices to apply architectural patterns
RWDG Slides: Governing Your Data Catalog, Business Glossary, and Data DictionaryDATAVERSITY
Data catalogs, business glossaries, and data dictionaries house the metadata that builds organizational confidence in your data. First and foremost, the people in your organization need to be engaged in leveraging the tools, understanding the data that is available and who is responsible for the data, and knowing how to get their hands on the data they need to perform their job function. This metadata will not govern itself.
Join Bob Seiner for the April RWDG webinar, where he will discuss how to govern the metadata in a data catalog, business glossary, and data dictionary. People must have confidence in the metadata associated with the data that you need them to trust. Therefore, the metadata in your data catalog, business glossary, and data dictionary must be governed. Learn how to govern that metadata in this webinar.
Bob will discuss the following subjects in this webinar:
• Successful Data Governance relies on value from very important tools
• What it means to govern your data catalog, business glossary, and data dictionary
• Why governing the metadata in these tools is so important
• The roles necessary to govern these tools
• Value expected from governing the catalog, glossary, and dictionary
The Ultimate Guide To Embedded Analytics Poojitha B
Did you know that the lack of in-context data prevents you from making smarter business decisions - and as a result, missing out on key revenue opportunities?
LoQutus helps organisations to innovate with analytics and to get insights with data visualisation. We also build large scale data layers to enable interaction with core data, and develop data-driven applications to deliver the insights our customers need. During this session we’ll share what we have learned along the way. We’ll show you our framework for self-service analytics & insights, and some successful case studies.
RWDG Slides: Using Tools to Advance Your Data Governance ProgramDATAVERSITY
Data Governance tools can be used to advance your Data Governance program … or they can become the reason why Data Governance fails to meet people’s expectations. Tools can be developed internally or acquired from reliable vendors to attempt to address your organization’s needs. Sometimes the best environment is made up of a hybrid of tools developed internally and tools acquired.
Join Bob Seiner for this month’s RWDG webinar where he will share tools that you can build yourself and talk about how the tools can be used to determine requirements to acquire outside tools. Tools developed internally at little or no cost have helped to solve many Data Governance problems. Several of these problems and their solutions will be described in detail during this webinar.
In this webinar, Bob will discuss:
• Several easy-to-build Data Governance tools
• Customizing these tools to address specific issues
• How internally developed tools can lead to tool acquisition
• Knowing when it is time to acquire tools
• Integrating DIY tools with acquired tools
7 steps for guides how to build a successful data strategyshopiawilson
Enterprise Data Strategy decisions and sets of choices that together, chart a high-level course of action to get high-level goals. Some important steps to build a successful data strategy.
Data Centric Development: Supercharge your web & mobile application developmentBright North
Many businesses are finding that their web and mobile applications aren’t providing the long-term solution they were hoping for. As consumers provide more and more useful data, these digital platforms don’t allow businesses to take advantage of the huge opportunities that data presents.
Our new whitepaper details the practical steps you can take to supercharge your web and mobile application development and stay ahead of the data revolution.
Slides: The Automated Business GlossaryDATAVERSITY
You can’t do business without being able to successfully extract insights from your organization’s data supply chain. You need a strong foundation for visibility and control of data. Flying by the seat of your pants, when it comes to analyzing your market, your performance, and your competitors’ performances, just doesn’t work.
In this webinar, we’ll examine the real-life daily struggles and frustrations plaguing the data supply chain and discuss how these struggles can be eliminated by automation of metadata operations such as data lineage, data discovery and business glossary.
When you attend this webinar, you will learn about:
• What data consumers are really spending their time on and why they are so frustrated
• The challenges of building a business glossary
• How to get started with an automated business glossary and why it’s critical for BI intelligence
Data Exploration and Analytics for the Modern BusinessDATAVERSITY
Every day, your business generates enormous quantities of data. How can you unlock its value? How can you build self-service exploration experiences that empower frontline decision-makers?
This webinar features Greg Jones from Smartling and Scott Hoover from Looker. Smartling is a powerful software platform for managing translation and localization of digital content. Looker is a data exploration platform that operates in the database. Together, Greg and Scott will introduce you to a modern approach to managing analytics in today’s fast-growing, web-centric business environments.
DataOps: Nine steps to transform your data science impact Strata London May 18Harvinder Atwal
According to Forrester Research, only 22% of companies are currently seeing a significant return from data science expenditures. Most data science implementations are high-cost IT projects, local applications that are not built to scale for production workflows, or laptop decision support projects that never impact customers. Despite this high failure rate, we keep hearing the same mantra and solutions over and over again. Everybody talks about how to create models, but not many people talk about getting them into production where they can impact customers.
Harvinder Atwal offers an entertaining and practical introduction to DataOps, a new and independent approach to delivering data science value at scale, used at companies like Facebook, Uber, LinkedIn, Twitter, and eBay. The key to adding value through DataOps is to adapt and borrow principles from Agile, Lean, and DevOps. However, DataOps is not just about shipping working machine learning models; it starts with better alignment of data science with the rest of the organization and its goals. Harvinder shares experience-based solutions for increasing your velocity of value creation, including Agile prioritization and collaboration, new operational processes for an end-to-end data lifecycle, developer principles for data scientists, cloud solution architectures to reduce data friction, self-service tools giving data scientists freedom from bottlenecks, and more. The DataOps methodology will enable you to eliminate daily barriers, putting your data scientists in control of delivering ever-faster cutting-edge innovation for your organization and customers.
ADV Slides: Increasing Artificial Intelligence Success with Master Data Manag...DATAVERSITY
Companies all over the world are going through a digital transformation now, which in many cases, is all about maturing the data environment and the use of data. Master data is key to this effort. All transformative projects require master data and usually many subject areas. Current efforts to deliver master data to the enterprise are cumbersome, inefficient, and met with limited acceptance.
We’ll look at enterprise use cases of artificial intelligence and show the master data that is needed. We’ll see what some MDM vendors are doing with AI and how the future of MDM will be shaped by looking at some specific MDM actions influenced by AI.
Introduction to Segment, Analytics API and Customer Data Platform. (Demo: Segment, AWS Redshift, Redash, Segment and GTM Alternatives) (Frontend Fighters Edition)
Recommended links:
https://segment.com/ - Analytics API and Customer Data Platform
https://open.segment.com/ - Open Source Projects of Segment
https://segment.com/docs/ - Documentation of Segment
https://redash.io/ - Open Sorce Data Dashboard
https://aws.amazon.com/redshift/ - Data Warehouse Solution
https://quicksight.aws/ - Business Analytics Service
https://www.ghostery.com/ - Tracker Detector
Keywords: business agility, tag managers, data-driven
Usually, DataOps means applying DevOps principles to existing data analytics projects. We accidentally reversed it, taking a DevOps initiative and catalyzing adoption of data-driven practices across our company.
What started as a practical initiative to bring better reliability and visibility to our software product had the unexpected effect of catalyzing a transformation that helped our organization become more data-driven across the company. What we learned in the process was how and why DevOps principles can naturally expand the role of a traditional operations team and bring wider culture change to the organization.
ADV Slides: Comparing the Enterprise Analytic SolutionsDATAVERSITY
Data is the foundation of any meaningful corporate initiative. Fully master the necessary data, and you’re more than halfway to success. That’s why leverageable (i.e., multiple use) artifacts of the enterprise data environment are so critical to enterprise success.
Build them once (keep them updated), and use again many, many times for many and diverse ends. The data warehouse remains focused strongly on this goal. And that may be why, nearly 40 years after the first database was labeled a “data warehouse,” analytic database products still target the data warehouse.
Advance Data Visualization and Storytelling Virtual WorkshopCCG
Join CCG and Microsoft for a virtual workshop, hosted by Senior BI Architect, Martin Rivera, taking you through a journey of advanced data visualization and storytelling.
Virtual Governance in a Time of Crisis WorkshopCCG
The CCGDG framework is focused on the following 5 key competencies. These 5 competencies were identified as areas within DG that have the biggest ROI for you, our customer. The pandemic has uncovered many challenges related to governance, therefore the backbone of this model is the emphasis on risk mitigation.
1. Program Management
2. Data Quality
3. Data Architecture
4. Metadata Management
5. Privacy
As digital channels continue to grow, they drive greater diversity in our data landscape. At Yorkshire Building Society, our purpose is to provide real help with real life and this relies on data from a myriad of sources. This diversity creates a need for points of intersection, where data can unite to feed customer and business insights. How do we create these hubs of intersection and what can modern technology offer?
Speaker:
Mark Walters
Lead Enterprise Data Architect for Data & Information
Yorkshire Building Society
This on-demand webinar will explore the challenges of working with legacy data and explain the technologies required to make that data a first-class citizen in modern cloud data environments while ensuring your costs don’t impact your business.
In this webinar viewers will understand:
- Challenges in integrating legacy systems with modern cloud data platforms
- Strategies for integrating legacy systems into a cloud architecture
- How Precisely Connect is helping customers to minimize costs while taking a modern approach to data integration
Bridging Legacy Systems and Cloud Data Platforms to Unlock Valuable Enterpris...Precisely
In this webinar users will understand:
- The benefits of data integration for driving business insights
- Challenges in integrating legacy systems with modern cloud data platforms
- Strategies for integrating legacy systems into a cloud architecture
- Benefits of real-time data replication with change data capture (CDC)
- How to future proof your data architecture
MWLUG2017 - The Data & Analytics Journey 2.0John Head
The typical perception of Big Data, Analytics, and Predicative/AI is that only the big companies can reap the benefits. Many believe they need a data warehouse, expensive reporting software, & an army of data scientists to get any value out of effort and cost. This session will explore and debunk that myth and showcase how companies of any size can participate. While there are many maturity models available, most are not designed to be practical guides to solving common business problems. Because of the explosion in cloud services, the barrier to entry has eroded significantly. We will look at some practical steps to access these capabilities and provide examples to where market-leading and growth companies have seen large benefits. Attendees will walk away with broader understanding of what’s possible to move their company through the journey in 2017. We will take a close look at IBM Watson solutions and how they integrate with IBM Collaboration and Social solutions.
Balance agility and governance with #TrueDataOps and The Data CloudKent Graziano
DataOps is the application of DevOps concepts to data. The DataOps Manifesto outlines WHAT that means, similar to how the Agile Manifesto outlines the goals of the Agile Software movement. But, as the demand for data governance has increased, and the demand to do “more with less” and be more agile has put more pressure on data teams, we all need more guidance on HOW to manage all this. Seeing that need, a small group of industry thought leaders and practitioners got together and created the #TrueDataOps philosophy to describe the best way to deliver DataOps by defining the core pillars that must underpin a successful approach. Combining this approach with an agile and governed platform like Snowflake’s Data Cloud allows organizations to indeed balance these seemingly competing goals while still delivering value at scale.
Given in Montreal on 14-Dec-2021
Alluxio Monthly Webinar | Five Disruptive Trends that Every Data & AI Leader...Alluxio, Inc.
Alluxio Monthly Webinar
Jan. 30, 2024
For more Alluxio Events: https://www.alluxio.io/events/
Speaker:
- Kevin Petrie (VP of Research, Eckerson Group)
- Omid Razavi (SVP of Customer Success, Alluxio)
2024 is gearing up to be an impactful year for AI and analytics. Join us on January 30, as Kevin Petrie (VP of Research at Eckerson Group) and Omid Razavi (SVP of Customer Success at Alluxio) share key trends that data and AI leaders should know. This event will efficiently guide you with market data and expert insights to drive successful business outcomes.
- Assess current and future trends in data and AI with industry experts
- Discover valuable insights and practical recommendations
- Learn best practices to make your enterprise data more accessible for both analytics and AI applications
In this webcast, Wayne Eckerson discusses the impact of artificial intelligence (AI) and machine (ML) learning on the finance industry, specifically how AI/ML will lead to augmented intelligence, in which man and machine collaborate to deliver optimal outcomes and decisions.
Watch the webinar on this link: https://www.youtube.com/watch?time_continue=506&v=UwBEd_m0XBs
Slide deck from our Cloud Saturday 2015 presentation. The session was a combination of case study and how to. We discussed how to build a fault tolerant SQL Server 2014 environment using Azure IaaS Virtual Machines.
In todays’ digital economy, enterprises expect more from the IT organization. They want applications delivered faster, and they want IT infrastructure to perform at a higher level than ever before. Consequently, IT operations must transform itself to better serve the business.
Llearn about top strategies for transforming IT in the digital era!
Get Loose! Microservices and Loosely Coupled Architectures DevOps.com
The recently published results from the 2017 State of DevOps Survey shows that loosely coupled architectures and teams are the strongest predictor of continuous delivery. Microservices and Containers are a great choice for creating these loosely coupled systems. But, many teams find it hard to decompose monolithic applications into Microservices, and they find it harder still to coordinate deployments and releases into the emergent “hyper-hybrid” operating environments.
Get Loose! Microservices and Loosely Coupled ArchitecturesDeborah Schalm
The recently published results from the 2017 State of DevOps Survey shows that loosely coupled architectures and teams are the strongest predictor of continuous delivery. Microservices and Containers are a great choice for creating these loosely coupled systems. But, many teams find it hard to decompose monolithic applications into Microservices, and they find it harder still to coordinate deployments and releases into the emergent “hyper-hybrid” operating environments.
TDWI Boston Keynote - The New BI/Analytics Synergy - 7 30-2015 - tdwi keynoteEckerson Group
To stay relevant in a fast-changing business and data environment, business and analytics leaders need to recognize that their teams are no longer the center of the data universe. They need to reach out and partner with other data analytics players in the organization and create a shared vision for the future. The new business analytics leader fosters a rich analytical ecosystem of people, processes and technologies that fuels a data-driven organization.
You Will Learn:
- How the data world has changed and why
- The cyclical nature of power in the data world
- Characteristics of the new analytical ecosystem
- The role of BI leaders and teams in the new world order
TDWI Boston Keynote: The New BI/Analytics Synergy Eckerson Group
To stay relevant in a fast-changing business and data environment, business and analytics leaders need to recognize that their teams are no longer the center of the data universe. They need to reach out and partner with other data analytics players in the organization and create a shared vision for the future. The new business analytics leader fosters a rich analytical ecosystem of people, processes and technologies that fuels a data-driven organization.
You Will Learn:
- How the data world has changed and why
- The cyclical nature of power in the data world
- Characteristics of the new analytical ecosystem
- The role of BI leaders and teams in the new world order
A Dynamic Data Catalog for Autonomy and Self-ServiceDenodo
Watch Daves' presentation on-demand from Fast Data Strategy Virtual Summit here: https://buff.ly/2Kj7muc
Denodo’s new dynamic catalog is the new black. It combines the power of data delivery infrastructure with data catalog for contextual information and collective intelligence.
Attend this session to discover:
• What is unique about Dynamic Data Catalog?
• How it empowers a community of analysts and decisions makers?
• How it facilitates data curation and data stewardship in your organization?
AWS re:Invent 2016: Effective Application Data Analytics for Modern Applicati...Amazon Web Services
IT is evolving from a cost center to a source of continuous innovation for business. At the heart of this transition are modern, revenue-generating applications, based on dynamic architectures that constantly evolve to keep pace with end-customer demands. This dynamic application environment requires a new, comprehensive approach to traditional monitoring – one based on real-time, end-to-end visibility and analytics across the entire application lifecycle and stack, instead of monitoring by piecemeal. This presentation highlights practical advice on how developers and operators can leverage data and analytics to glean critical information about their modern applications. In this session, we will cover the types of data important for today’s modern applications. We’ll discuss visibility and analytics into data sources such as AWS services (e.g., Amazon CloudWatch, AWS Lambda, VPC Flow Logs, Amazon EC2, Amazon S3, etc.), development tool chain, and custom metrics, and describe how to use analytics to understand business performance and behaviors. We discuss a comprehensive approach to monitoring, troubleshooting, and customer usage insights, provide examples of effective data analytics to improve software quality, and describe an end-to-end customer use case that highlights how analytics applies to the modern app lifecycle and stack. Session sponsored by Sumo Logic.
AWS Competency Partner
The Data & Analytics Journey – Why it’s more attainable for your company than...John Head
The typical perception of Big Data, Analytics, and Predicative/AI is that only the big companies can reap the benefits. Many believe they need a data warehouse, expensive reporting software, & an army of data scientists to get any value out of effort and cost. This session will explore and debunk that myth and showcase how companies of any size can participate. While there are many maturity models available, most are not designed to be practical guides to solving common business problems. Because of the explosion in cloud services, the barrier to entry has eroded significantly. We will look at some practical steps to access these capabilities and provide examples to where market-leading and growth companies have seen large benefits. Attendees will walk away with broader understanding of what’s possible to move their company through the journey in 2017. We will take a close look at IBM Watson solutions and how they integrate with IBM Collaboration and Social solutions.
The Data & Analytics Journey – Why it’s more attainable for your company than...LetsConnect
The typical perception of Big Data, Analytics, and Predicative/AI is that only the big companies can reap the benefits. Many believe they need a data warehouse, expensive reporting software, & an army of data scientists to get any value out of effort and cost. This session will explore and debunk that myth and showcase how companies of any size can participate. While there are many maturity models available, most are not designed to be practical guides to solving common business problems. Because of the explosion in cloud services, the barrier to entry has eroded significantly. We will look at some practical steps to access these capabilities and provide examples to where market-leading and growth companies have seen large benefits. Attendees will walk away with broader understanding of what’s possible to move their company through the journey in 2017. We will take a close look at IBM Watson solutions and how they integrate with IBM Collaboration and Social solutions.
Similar to Managing Data Sprawl with Data Catalogs for Self-Service (20)
Effective tips for leaders in the #BI and #Analytics space who want to become better leaders.
Visit www.eckerson.com to know more about our research, education and consulting services.
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.