Traditional business intelligence (BI) and analytic models are being disrupted as the balance of power shifts from IT to the business, according to Gartner, Inc. The rise of data discovery, access to multistructured data, data preparation tools and smart capabilities will further democratize access to analytics and stress the need for governance. Gartner predicts that by 2017, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis. Last week when I was going through research reports I found some interesting facts that I would like to share in this article.
The transformation of Business Intelligence (BI) from an IT-centric, centralized process to a self-service, decentralized process is clear:
- According to Gartner, “By 2017, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis”
- Forrester’s top prediction for BI is, “Managed BI Self-Service Will Continue to Close the Business and Technology Gap.”
- Forbes reported, “Visual data-discovery, an important enabler of end user self-service, will grow 2.5 x faster than the rest of the market, becoming by 2018 a requirement for all enterprises.”
What is surprising is the form that self-service BI in the hands of end users will ultimately take. Traditionally, self-service analytics options were based on Data Discovery tools: search, visualizations, dashboards, data mashups, etc.
Self-service BI provides an environment in which it is easy to discover, access, and share information, reports, and analytics. Information workers want to be able to personalize their dashboards or have automated BI capabilities so that the information becomes actionable for their particular situations. It must also be in an easy-to-use format and delivered to a device and user interface of their choosing.
The efficacy of discovery tools such as interactive visualizations and dashboards has helped to shift the focus of self-service BI from numeric representations to graphic images. 2015 will see the natural progression of this shift from images to data-driven narratives that explicate analytics results. Doing so requires a greater amount of specificity of visualizations and their settings, as well as the inclusion of textual accompaniments of analytics results.
Self-service BI offers an environment in which information workers can create and access specific sets of BI reports, queries, and analytics themselves—without IT intervention. This approach extends the reach and scope of BI applications to address a wider range of business needs and problems. At the same time, this extension must support the information workers’ need for a personalized and collaborative decision-making environment. Information workers must become more self-sufficient by having a BI environment that is more usable and more consumable. It is these two themes—usability and consumability—that play crucial roles in a fully functioning self-service BI (SS BI) environment.
Self-service BI shifts the emphasis away from the processes required to manage data in a centralized store and toward a process for finding, accessing and integrating pertinent information as needed. With self-service BI, decision makers are better able to respond to changes in business conditions quickly.
As per forester report Tableau Software continues to set the standards for self-service advanced data visualization. Self-service and intuitive data visualizations go hand in hand, and Tableau has been the vanguard of advanced data visualization for years. Late last year, Tableau closed a functionality gap with the introduction of an in-memory engine for data discovery and exploration. The new capability gives two important options for business users: the ability to load the entire data set into memory and perform highly responsive data exploration or, if the data set is too big, leave data where it is — in a relational or multidimensional DBMS — and analyze it with Tableau’s patented and intuitive VisualSQL. It reminds me our recent Tableau implementation for a leading insurance company where we helped them eliminate 20% of the legacy reports.
Not all integration tools that expedite the data preparation process accompany Business Intelligence offerings; there are a number of standalone options as well. However, 2015 will definitely see the assertion of self-service BI and the gradual receding of centralized, IT department based models.
To know more about our analytics practice and share your data needs email us at firstname.lastname@example.org