Only 11% of business intelligence (BI) and analytics users consider open source critical. Despite sitting squarely in a minority, those people outperform the other 89% on many key measurements. They report significantly more instances of:
- BI and analytics budget increases
- The highest level of success with BI initiatives
- Data leaders in place
- The two highest levels of data literacy
- Making data-driven decisions all the time
So how can organizations become more open-source literate with their data analytics infrastructure? Find out in this latest report from Dresner Advisory Services.
- Only 11% of the surveyed organizations deem open source as critical to their analytics and BI initiatives going forward. However, that minority outperforms the other 89% in many important measures.
- Organizations that view open source as critical report more instances of increasing BI and analytics budgets, and fewer instances of flat and decreasing budgets.
- Those who consider open source critical most frequently come from both the smallest and the largest organizations.
- Organizations that view open source as critical are 39% more likely to have a data leader and 26% less likely not to have a data leader (compared to all other organizations).
- Organizations that view open source as critical report having the two highest levels of data literacy almost twice as often as all other organizations.
- Organizations that view open source as critical express a slight preference for best-of-breed build-your-own environments, compared to single-vendor integrated BI platforms.
- Organizations that see open source as critical are more likely to have everyone using spreadsheets.
Read Previous Reports
- Part One: The State of BI, Data, and Analytics in Financial Services in 2022
- Part Two: Making Data Easier to Find, Access, and Use Should Start With a Data Catalog
- Part Three: Time to Take Ownership and Align Spreadsheets With Your Data Strategies and Programs
- Part Four: Cloud BI: Think Big, Think Small, Act Rationally
- Part Five: The Evolution of Demand for Master Data Management