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UID:4@rishisapra.com
DTSTART:20240323T101500Z
DTEND:20240323T110000Z
DTSTAMP:20250413T084141Z
URL:https://rishisapra.com/events/sql-bits-2024-what-does-microsoft-fabric
 -mean-for-a-finance-business-analyst-50-minute-session-free-community-day/
SUMMARY:SQL Bits 2024 - What does Microsoft Fabric mean for a Finance/Busin
 ess Analyst? (50 minute session\, Free community day)
DESCRIPTION:Running since 2007 and now with over 3\,000 attendees\, SQL Bit
 s has become the largest Data Platform conference in the world\, running a
 nnually and featuring 200 world class speakers\, 300+ hours of content\, a
 nd the best networking opportunities in the industry. It features the worl
 d's best experts in the Microsoft data space presenting and attending from
  across the world.\n\n​I presented a session on what Microsoft Fabric me
 ans for a Finance/BI Analyst.\n\n​\n\nWe started with looking at how fin
 ancial reporting has evolved over time towards being more self-service dri
 ven with Power BI\, and some of the challenges this presents when not supp
 orted by a cloud data platform. (Transactional finance data in particular 
 needs a lot of work to be used for analytical purposes and this needs to b
 e done in an auditable\, scalable and performant manner!).\n\nWith the nee
 d for a data platform established\, we looked at how Microsoft Fabric brin
 gs much of this capability back into the hands of technically minded finan
 ce staff who are now able to self-serve on the entire analytics process. W
 e will explore the concepts of lakehouses and OneLake being the single loc
 ation for all finance data (rather than much of it being kept in local Exc
 el files!) and considered the benefits of all analytical workloads being a
 ble to utilise this data without having to duplicate it.\n\nFinally we loo
 ked at how Fabric needs to be implemented across the Finance and IT functi
 ons in order to reap its benefits. This includes getting the right operati
 ng model (based on data mesh or CoE models) and considering the needs and 
 skillsets of different individuals who work with data (e.g Data Explorers\
 , Data Analysts\, Data Engineers and Analytics Engineers!).
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