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From Data Prep to Finance Reporting: 3 Examples to Speed Up Analysis

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Financial data is messy. Preparing and transforming financial data for analysis is highly manual and time-consuming. With the extensive cleaning and shaping that happens with financial data, how do you build trust and confidence in your data, making it credible, once it’s been exported out of your source systems? Landing all of your data into a secure and managed database is a necessary part to reaching optimal confidence in your data and likely on your roadmap, but probably several months or years from being a reality. Before you’ve partnered with IT to create this database, there are processes you can build today to improve your finance data validation and preparation. These processes will help your team reduce risk by automating manual processes to find errors faster—before you’ve closed the books and before your accounting or audit team finds them. In this whitepaper, we’ll share methods to spark ways your team can improve operational efficiencies. Read about how the Tableau finance analytics team did this by structuring tie outs to source systems, dashboards that validate data incrementally, and examples of workflows to improve data preparation.

With prepared financial data that builds credibility with your stakeholders, your team can focus on higher value work like analysis and forecasting, instead of manual tasks. When performing as a strategic partner to the entire enterprise, building confidence in financial data and reporting is everything. Your stakeholders might make business decisions off of bad data, but with faster, more accurate data preparation process, you won’t let them.

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About Tableau

Tableau helps people transform data into actionable insights. Explore with limitless visual analytics. Build dashboards and perform ad hoc analyses in just a few clicks. Share your work with anyone and make an impact on your business. From global enterprises to early-stage startups and small businesses, people everywhere use Tableau to see and understand their data.

Featured In

Fast Company
Wallstreet Journal