The 2023 Ventana Research Buyers Guide for Collaborative Analytics research enables me to provide observations about how the market has advanced.
Analytics almost universally involves collaboration among a team of individuals. Interpreting the results of the analyses, choosing a course of action and tracking the implementation of
Capabilities that support the sharing of — and communication about — output from analytical processes help organizations maximize the value of their analytics investments. Facilitating communication and collaboration among those involved in the decision-making process leads to more informed and better decisions. Our research shows that nearly four in 10 organizations are using collaboration to support analytics processes, and more than one-half said they expect to use these capabilities in the future. Analytics and BI vendors have recognized the value of collaboration and have increasingly been incorporating these capabilities into their products.
More than a decade ago, social media tools like Facebook, Twitter and LinkedIn brought on a wave of collaborative analytics and BI capabilities. We saw chat streams associated with specific analyses that users could like or endorse. The number of contributions a user made to the community was part of his or her profile so others could accordingly weigh the importance of the input. However, after an initial surge of interest, these efforts failed to gain traction and waned.
Collaboration requires a large community of active individuals, and there simply were not enough people regularly engaged in using the analytic products. Those early efforts also required users to participate in the dialog from within the analytics and BI products. Rather than working solely with those products, line-of-business personnel spend their days using a variety of business applications.
Two major changes now provide the glue to pull a community of collaborators together: mobile devices and enterprise collaboration tools. The significant expansion of mobile analytics and BI has made it easier for users to get involved. Perhaps more importantly, in the same way the social media users get notifications of activity via mobile devices, collaborative analytics and BI vendors use mobile notifications to engage participants in the analytics process. Organizations have also adopted more widespread use of enterprise collaboration technologies in place of or in addition to email and is more widely available.
The analytics process typically involves multiple people with differing areas of expertise and responsibilities. Collaborative tools can enable this diverse group of participants to coordinate their activities and share knowledge. To be most effective, collaborative capabilities should cover the entire data and analytics process; only this way can participants understand the provenance of data as it is analyzed.
With this approach, it is easy to identify subject matter experts to engage in the dialog. The team can discuss and document decision-making for compliance purposes, and the actions
As organizations embrace more sophisticated analytics such as artificial intelligence (AI) and machine learning (ML), and as analytics become more easily accessible via technologies such as natural language processing (NLP), collaboration capabilities will become even more important. However, strong collaboration capabilities alone are insufficient. These capabilities also must include strong analytics. Our Value Index assessment methodology takes all these factors into account.
This research evaluates the following vendors that offer products that address key elements of collaborative analytics as we define it: AWS, Cloud Software Systems, Domo, GoodData, Google, IBM, Idera, Incorta, Infor, insightsoftware, Microsoft, MicroStrategy, Oracle, Pyramid Analytics, Qlik, SAP, SAS, Sigma Computing, Sisense, Tableau, ThoughtSpot and Zoho.
You can find more details on our site as well as in the Buyers Guide Market Report.
Regards,
David Menninger