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Stop guessing and try data-driven business decisions instead
It’s time to abandon uninformed guessing about what has happened and what to do next and move toward true data-driven business decisions. That should be a top priority for all organizations, according to TDWI’s David Stodder.
In his TDWI Best Practices Report: Visual Analytics for Making Smarter Decisions Faster, Stodder says business users really want to move past the limits of spreadsheets and canned BI reports. And he explains how one of the hottest trends today, visual analytics, can help everyone gain a richer, more personalized experience with data for improved decision making.
This infographic showcases some of the key statistics and findings from TDWI’s Best Practices Report: Visual Analytics for Making Smarter Decisions Faster. (Click to enlarge.)
Stodder says the trend toward visual analytics is fed by the demand for easier capabilities for nontechnical subject-matter experts – those who want to analyze data more frequently and need a better way to discover and share insights, with less IT oversight.
Here are his top 10 recommendations for using visual analytics to drive data-driven business decisions.
1. Make self-service visual analytics and data discovery a priority but ensure users understand new responsibilities.
You don’t want things to fly out of control. Governance, data quality, data lineage, data definitions and metadata are important for users to understand in their quest for unencumbered data discovery. Centers of excellence and governance committees can help clarify and assign responsibilities.
2. Don’t let IT become the roadblock; develop a strategy to address IT concerns about self-service.
Fostering dialogue between IT and business users about how to enhance freedom for adoption of self-service BI and visual analytics tools is imperative for making data-driven business decisions more egalitarian.
3. Aim for “managed” or “governed” self-service with business-focused analytical applications.
Organizations will need to find the right balance between user freedom and flexibility and proper observation of data security, privacy and regulatory policies. Again, it’s all a balance.
4. Provide training and education opportunities for users who seek to do more with advanced analytics.
TDWI’s report found that users are most successful in using BI and visual analytics tools to build dashboards and scorecards. But many could benefit from incorporating more advanced analytics into their work. Help them learn how.
5. Put delivering upper management insights high on your priority list.
The TDWI research found that satisfying executives is the most important benefit organizations hope to achieve through the use of business intelligence and visual analytics. Make it number one on your to-do list.
6. Take advantage of in-memory computing to improve performance and data availability.
Evaluate needs for in-memory computing and take advantage of it for highly interactive and iterative visual analytics. Computing answers on the fly makes faster data-driven business decisions possible.
7. Make self-service data preparation part of the visual analytic experience if the technology can support it.
According to the TDWI survey, IT is still largely responsible for data preparation in most organizations. New technologies are increasing the options for self-service data prep, which could take some of that pressure off of IT.
8. Use visual analytics to support data storytelling for smarter and faster decision making.
Educate and train users to move beyond simply presenting reports or isolated visualizations to tell a fuller story of the data exploration and analysis.
9. Evaluate cloud and SaaS options to gain visual analytics advantages without infrastructure commitment.
According to the TDWI report, neither cloud nor SaaS are in widespread use yet, but organizations should evaluate them as an opportunity for users to try out tools and build prototypes without additional infrastructure investments.
10. Integrate visual analytics, including embedded functionality, into strategies for decision management.
Organizations that need to manage a high volume of real- or near-real-time decisions can benefit from decision management, an integrated technology and approach to intelligent automation of decisions. Visual analytics can help identify these opportunities.
Read the full TDWI Best Practices Report, Visual Analytics for Making Smarter Decisions Faster: Applying Self-Service Business Intelligence Technologies to Data-Driven Objectives to learn more.
- Want visual data discovery and easy-to-use interactive predictive analytics in a collaborative environment? Read this white paper to find out how SAS delivers.
- Wayne State University pairs data visualization and Hadoop for data-driven business decisions.