Deploying Flexible, Self-Service Analytics

With Multiple Data Sources and Many Users

Today it’s common for businesses to need to analyze data from many and disparate sources. This makes it challenging for the IT team to provide intelligence across incompatible systems and different formats. The job is further complicated when different systems show different data, and questions arise over what is accurate. And finally, different users need different levels of flexibility to work with their data.

In their desire to quickly give managers reports, some IT teams try to anticipate mangers’ needs, gather data and create custom reports and dashboards they think mangers will use based upon past requests. But this approach often fails because IT managers don’t think like managers running manufacturing floors, warehouses, multiple retail outlets or project development teams. The reports aren’t used because they lack the insight the mangers need, or it goes through multiple revisions to get it “just right.” And when the business changes as it invariably will, the reports need to be revised again.

Either way, it’s a cumbersome process fraught with delays that often leaves mangers unable to interact and receive their data in a meaningful and timely manner.

Download to learn:

• How to address business users’ need for information while reducing load on the IT team
• How to reduce cycle time and improve accuracy for reports
• The benefits of using a single data presentation layer for multiple data sources
• Best practices for understanding the needs of your users and deploying flexible, self-service business intelligence

In this whitepaper you’ll see how one IT team at a fast-growing company that serves a network of thousands of distributors provided their users with flexible, self-service business intelligence that resulted in reduced turnaround time and improved accuracy for reports.