Sberbank CZ: Tableau transforms our data into real information for decision making
How it was
More time for data analysis
Thanks to the deployment of Tableau, the time required to prepare reports was reduced. Data is now loaded directly into individual reports and dashboards, eliminating the need to check for accuracy when preparing them. Thus, more time can be devoted to data analysis and interpreting their noteworthy connections with potential business impact.
Start for further development
The project was not only about the technological aspect, but also about ensuring the adequate development of human resources in the area of data competence. Applications in individual areas were developed in close cooperation with the bank's expert guarantors in order to prepare the conditions for their further internal development both in terms of automation and adaptation to new needs.
Same data for all
Discussions about who has the right data are a thing of the past. Users access the same set of data at any given time through the application. This enables management processes to take place over one version of the truth and allows them to focus on the root of the problem. In addition, the connection to centralized access control provides a higher level of security for sensitive internal data.
Tableau's vast data visualization capabilities allow you to tailor the reporting format to the target audience: from overview dashboards for top management (previously created manually in Power Point) to drill-down reports for lower levels of management (regional managers, branch managers, bankers).
Head of Financial Controlling & Reporting
Although we do not yet have a 100% complete data base and data warehouse, we have decided to start from the user interface over the data that is available. We want to provide business users with a unified environment for reporting, dashboards and analytics that will actually use the data, and thus generate interest in the data. I see this as a better way to achieve true adoption of data-driven decision making than the opposite approach of building a quality data base.