Less requirements gathering, more data exploration

Traditionally onerous tasks in information management initiatives are being rendered obsolete by hands-on collaborative methods.

“We pull data into prototypes so the business can give immediate feedback. That speeds things up, makes it more exciting for everybody, and saves a tremendous amount of time.”

—Philip Russom, director of TDWI Research

Requirements gathering. For any typical information management program, these two words often signal weeks—even months—of effort. You work to determine the data necessary for a new project, only to discover the data doesn’t work or the original needs have changed. If you’re one of the many business analysts spending as much as 23 percent of your time on this time-consuming process1, you're ready for a better approach to requirements gathering. You’re ready for data exploration.

“We don’t even call it ‘requirements gathering’ anymore—that’s fading away. Now we take for granted that we can all look at data directly. We pull data into prototypes so the business can give immediate feedback. That speeds things up, makes it more exciting for everybody, and saves a tremendous amount of time,” says Philip Russom, director of TDWI Research, during February’s “Great Data by Design I: Agile Data Integration and Holistic Data Stewardship” Informatica Talk.

Rethinking people, process, and tools

Russom points out that data exploration requires innovation in two areas: the data management tools you use and the processes that guide their use.

First, you need to have modern, user-friendly tools that enable data exploration. Key features include:

  • Data profiling and discovery
  • Data visualization
  • Advanced analytics
  • Reporting

Data exploration tools must enable easy collaboration among business analysts, developers, and the business users who request the data. All of these stakeholders must be able to work side-by-side on dashboards, share screens across the network, and save and share their work asynchronously through the same tool.

Second, you need to identify a partner—ideally an expert data steward—from the business to work with on each new project. When IT and business collaborate with data exploration tools, you can slash weeks from the requirements-gathering process. Communicating directly about the data gives you better insight into the needs of the business and can help you propose better solutions in the future.

With the right tools, you and the business users can easily explore your organization’s data and find exactly what data the business needs to analyze. You can also establish standards for using data and require everyone to stick to those standards. Because data profiling is built into data exploration tools, you can more readily reuse data profiles.

Keeping it real

“There are a lot of advantages to data exploration—it’s not just the time savings,” says Russom. “You’re working with real requirements and real data, so you can show the user the data in the visualization or dashboard tool they're going to use.”

According to Russom, keeping it real may be the biggest advantage to data exploration over traditional requirements gathering. When the business can choose only from existing attributes, it sets reasonable expectations. Exploration reminds everyone that the parameters for data requirements are bound by the data that you’re currently gathering. On the other hand, exploration can help you and your colleagues identify new types of data that you should begin collecting.

By phasing out traditional requirements gathering in favor of data exploration and collaboration with business users, you can more accurately align your efforts with the business requirements. This not only makes your efforts for gathering requirements more nimble, but will support your organization’s move toward agile data integration.

For real-world insight into the importance of a collaborative approach, read Potential at Work’s interview with Barbara Latulippe, senior director of enterprise data governance at EMC.

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