Maveryx Success Stories
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SUBMISSION INSTRUCTIONSAnalytic Transformation at Fannie Mae
In 2018, Fannie Mae decided to retire an existing BI tool and migrated all their legacy reports to a new source. The Business Intelligence team had to convert and enhance 30 dashboards in an aggressive six-month time frame, while combining several data sources and preserving numerous complex financial calculations. With Alteryx, they accomplished their task and reduced process time by 75%, improved performance, and time to market.
Our goal was to manage a legacy reporting conversion in a tight deadline, without losing key functionality. While the timeline was a major concern, our team was also presented with several challenges, such as data preparation, report complexity, collaboration difficulties, and project scheduling.
When looking at the legacy reports, data was being inputted by up to ten sources for a single report and many of the visualizations had custom code which needed to be rewritten. Additionally, there were very complex financials formulas nestled within these reports which needed to be included in the new solution. These factors made our conversion significantly more intricate.
In addition to report complexities, another concern was collaboration across multiple different teams in various geographies. Our developers had to travel to Washington D.C. to meet business users, capture requirements, and ensure we created our new reports based on the same criteria and functionality. This added an extra layer of complication and required additional time to schedule. On top of all this, we needed to document our training materials for end-users and future efforts.
How did we approach this conversion? Our starting point was completing a proof of concept, which tested our process on a small set of legacy reports to determine how to best convert these reports using new tools. Once confirmed, we needed to determine which reports would be converted based on business need. We discovered close to 40 dashboards required conversion, so we evaluated based on business importance and created a prioritized structure.
With our process confirmed and priority set, we could start focusing on creating the new reports. The legacy reports had multiple data sources including Netezza, Oracle, SQL Server, and Excel files, so we performed a comprehensive gap analysis to document the current state reporting process and considerations that needed to be included in our future state. All this planning provided the team with a strategy to best execute and finalize the technical architecture for our project.
Alteryx was huge in our data preparation efforts and fed directly to the new BI tool, MicroStrategy. Our team made strategic decisions on where to utilize Alteryx versus MicroStrategy and looked at the various calculations and outputs to develop an identical solution. We decided all our use cases and reports would route to Alteryx, where joins and advanced calculations were completed and output files were sent to the correct databases. From there, we created tables to connect to MicroStrategy and Tableau.
Ultimately, we met our deadline and cut the time to execute our report from 40 to 10 minutes, which was a big achievement. This occurred mainly because all the joins and calculations were done in Alteryx and required less processing time to complete. The report now inputted from 10 different data sources and increased the number of complex calculations. Lastly, we successfully decommissioned our legacy reports.
After six months, we converted over 30 dashboards, while improving performance and time to market. Alteryx empowered us to connect our data and utilize functionality such as joins, complex calculations, and separate preparation from our BI tool. Additionally, we created a knowledge base for reference, training, and tips/tricks for maintenance. This has become increasingly important for training business users and is best practice from an organizational efficacy perspective.
While we achieved our initial objective, some of our most important benefits were the lessons learned. We can now plan more accurately, set more realistic deadlines, and be much better equipped to support our organization using our analytic tools.
