How Information Managers Can Explain Usage Data Through Visualizations

Before planning the future of your information center, you need to understand the past. While not a crystal ball, predictive analytics help organizations forecast future events by finding patterns and trends in historical data. With this type of information more readily available than ever before, understanding the past has become much easier.

Deciphering how predictive analytics and business intelligence (BI) impact organizations is the subject of a recent report published by Dresner Advisory Services. 2017 Advanced and Predictive Analytics Market Study comprises 90 pages of in-depth market analysis, examining evolving user perceptions and future capabilities.

How, when, and why business intelligence is being used

An article in Forbes identifies key points from this global report, which is based on insights from more than 3,000 organizations. Here’s a look at the takeaways information managers should know, as they look to utilize data to tell their content ROI story.

End-user self-service is a top priority 

When it comes to advanced analytics, perhaps unsurprisingly, BI experts, business analysts, statisticians and data scientists are the most frequent users. Just over 60% of data scientists and statisticians reported using these tools either constantly or often. At the other end of the table, executives and third-party consultants were found to use the technology the least.

Remember: Just because executives aren’t working with BI technology, doesn’t mean they’re not utilizing the data found within it. Many times, information managers must compile and analyze data, and bring forth the most important trends or insights to upper management. In these situations, having a clear understanding of what your stakeholders will want and need to see is critical.

Learn more: Defending Content Spend – Make Sure You Involve the Right People

Reporting capabilities and dashboards are “must-haves”

It’s still early days for many of the technologies driving BI and predictive analytics, but the study revealed that companies are acknowledging their importance for future growth and are investing accordingly.

The top two priorities for enterprises planning to utilize BI data are reporting capabilities and dashboards; 80% of respondents consider these to be “critical” or “very important.” Within dashboards, end users can organize the data they find most valuable, making it easier to showcase to stakeholders and other departments within the organization.

Data mining, data discovery and data storytelling also featured highly, with more than 40% of respondents deeming them as critical or very important.

Additional takeaways:

Scalability: Regarding predictive analytics and business intelligence platforms, in-memory and in-database analytics come out on top, with more than 80% of respondents considering them to be important.

Features of analytics technology: The study also revealed that organizations are basing their BI initiatives on features within the technology. Around 80% of respondents rank regression models, textbook statistical functions, and hierarchical clustering as the most important features. Given less importance are text analytics functions and sentiment analysis (less than 70%), and ensemble learning (less than 60%).


As the volume of data continues to grow, so too does investment in advanced analytics tools, data scientists, and their ongoing skills training.

Not sure how analytics could help your information center? Check out RightFind Business Intelligence. 


Author: Casey Pickering

Casey Pickering is a Product Marketing Manager in CCC’s Publisher Business Unit. Casey develops go-to-market strategies, conducts market research, creates customer personas, drives strategic marketing efforts, and develops product positioning to drive interest in our product offerings. A passionate Boston sports fan, Casey is a graduate of Northeastern University and enjoys spending time outside with her family including her Bernese Mountain Dog, Riggins.
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