As employees increasingly require autonomy to access and manipulate data, companies must evolve their use of analytics solutions. Self-service data discovery tools present the opportunity for organizations to meet these needs by providing consumer-grade usability. However, usability itself is not enough. As the need for incorporating data analysis into business decisions increases, companies must couple self-service access with governance and scalability.
This report examines the challenges and evaluation criteria of three organizations looking to address gaps in their existing analytics. The research subjects included a multi-national biotechnology firm, a global petrochemical firm, and a mid-sized financial services firm. And although unique in industry, they shared common challenges including:
Organizational Challenges and Investment Drivers
- Legacy solutions were designed for centralized control. This made it difficult to handle a large and growing number of analytics requests.
- Often, Microsoft Excel was the default reporting tool. This limited the complexity of the analysis that could be performed, and created errors and delays due to manual updating.
- Organizational data existed in silos, making it difficult to gain the “full picture” when conducting analysis.
Participants cited a range of factors contributing to their investment in a self-service data discovery solution. The acquisition drivers that they identified in common included the need to expand data access to more employees and to support stronger analytical capabilities across the enterprise. In addition, some participants identified a need for analytic collaboration and improved efficiency as key criteria for investing in a new solution.
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