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SkillsCast

Lessons from the Enterprise: Managed Self-Service BI at Global Scale

3rd June 2019 in London at CodeNode

This SkillsCast was filmed at Power BI June

Self-service BI tools are sometimes described as a two edged sword. SSBI is a powerful tool for solving common problems at scale, but it can also introduce new challenges as more users are empowered to work with more data. There is no one "right" or "best" way to deliver managed self-service capabilities, but there are common patterns and approaches that successful teams apply. In this session, Matthew Roche from the Power BI CAT team will present patterns and practices learned from from conversations with over 100 global enterprise organizations. If you're already struggling with challenges from self-service BI, if you're tasked with establishing a BI center of excellence and don't want to reinvent the wheel, or if you just want to a head start to understand the road ahead, join Matthew to learn from those who have gone down that road before you. This a new session. The target audience is IT and business stakeholders who are trying to balance centralized enterprise BI and flexible self-service BI in large or large-ish organizations. Pro tip: Two-edged swords are the best type of sword.

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Lessons from the Enterprise: Managed Self-Service BI at Global Scale

Matthew Roche

Senior Data Warrior Matthew Roche is a Senior Program Manager in Microsoft’s Cloud + AI Group, where he focuses on business intelligence, enterprise information management, metadata, and data warehousing. Matthew is currently a member of the Power BI CAT team, where he was saddened to learn that there were not actually any cats. Previously Matthew has worked on Azure Data Catalog, SQL Server Integration Services, Master Data Services, and Data Quality Services. Before joining Microsoft, he worked as an architect, consultant, and trainer focusing on ETL, data warehousing, and business intelligence. When he’s not enabling the world to get more value from its data, Matthew enjoys reading, baking, heavy metal, and competitive longsword combat.

SkillsCast

Self-service BI tools are sometimes described as a two edged sword. SSBI is a powerful tool for solving common problems at scale, but it can also introduce new challenges as more users are empowered to work with more data. There is no one "right" or "best" way to deliver managed self-service capabilities, but there are common patterns and approaches that successful teams apply. In this session, Matthew Roche from the Power BI CAT team will present patterns and practices learned from from conversations with over 100 global enterprise organizations. If you're already struggling with challenges from self-service BI, if you're tasked with establishing a BI center of excellence and don't want to reinvent the wheel, or if you just want to a head start to understand the road ahead, join Matthew to learn from those who have gone down that road before you. This a new session. The target audience is IT and business stakeholders who are trying to balance centralized enterprise BI and flexible self-service BI in large or large-ish organizations. Pro tip: Two-edged swords are the best type of sword.

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Thanks to our sponsors

About the Speaker

Lessons from the Enterprise: Managed Self-Service BI at Global Scale

Matthew Roche

Senior Data Warrior Matthew Roche is a Senior Program Manager in Microsoft’s Cloud + AI Group, where he focuses on business intelligence, enterprise information management, metadata, and data warehousing. Matthew is currently a member of the Power BI CAT team, where he was saddened to learn that there were not actually any cats. Previously Matthew has worked on Azure Data Catalog, SQL Server Integration Services, Master Data Services, and Data Quality Services. Before joining Microsoft, he worked as an architect, consultant, and trainer focusing on ETL, data warehousing, and business intelligence. When he’s not enabling the world to get more value from its data, Matthew enjoys reading, baking, heavy metal, and competitive longsword combat.