Charting the Evolution of Self-Service Business Intelligence

Companies of all sizes are harnessing the power of self-service BI, next-generation data management, and embedded analytics to achieve greater ease of use and faster and better access to information and insights. Even large corporations are adopting best-of-breed self-service solutions to supplement their core business intelligence initiatives, providing a friendlier front end that builds on their existing investments. Self-service BI means giving non-IT business users the tools they need to gain full, governed control over their data. By being able to visually explore, prepare and transform their data into performance dashboards and customized reports, according to their exact specifications, they can get the answers they need at a glance and make smarter, more timely business decisions. Large companies have a lot to gain by implementing relatively inexpensive tools that allow business users to consolidate data on the fly and present it in a visually meaningful way. For smaller companies, self-service BI tools may be the only solutions they will ever need.

Self-service BI capitalizes on the fact that today the smallest tablets, and even smartphones, come with powerful processors and many gigabytes of memory. That makes it possible to perform analytic tasks in the palm of your hand that only a few years ago would have required a server. The best self-service BI solutions require that users possess no more skills than they need for Excel, yet they deliver deeper insights, faster and in far more accessible ways. These tools can pull data from existing BI systems, extract it on-the-fly from spreadsheets or from any number of data sources.

Aside from the explosion in processing power and mobility, several other forces have converged to set the stage for next-generation self-service BI. These include the proliferation of big data, both structured and unstructured. The diversity, velocity and sheer volume of data has increased by orders of magnitude in recent years. Data comes from point-of-sale, marketing, sales and ecommerce applications. It comes from customer feedback forms. It comes from call centers and social networking apps. It comes from website and mobile device logs. And the list goes on. Meeting the needs of business users means being able to connect to data, whatever its source and wherever it may reside.

Today the rapid evolution of flexible database infrastructures and the advent of cloud-based interfaces and interactive visualization tools can bring data to life in a dazzling array of color-coded charts, funnels, pies, spider webs, maps and various other configurations. Anyone can easily navigate, manipulate and analyze the data using check boxes, radio buttons, sliders, lasso filtering, zooming, attribute highlighting and countless other types of drill-down mechanisms and data filtering features using a fixed or variable-driven connection to predefined data sources. More advanced users can combine new data sets and create new metrics and dimensions.

The establishment of technology standards is an important factor in the evolution of self-service BI. These standards make it easier than ever to integrate data stored in a company’s on-premise data center, data from third-party sources, data in the cloud, and data from virtually any business app. Hadoop, in particular, is a widely-adopted open source software framework designed to query large data sets stored in a distributed fashion. At the same time, APIs have migrated en mass from client/server programming to standards like JavaScript, which provides the technology backbone for generating rich visualizations and embedding BI functionality into third-party apps. Next-generation BI solutions are also largely build on client-side development frameworks, such as React.js and AngularJS, and responsive technologies, such as AJAX and jQuery. These technologies, together with cloud-based deployment features, enable a dynamic Web and mobile experience and allow for highly extensible and customizable options.

When it comes to accessing information, generating insights and driving continuous performance improvement, self-service BI can rightly be viewed as a game changer. This is true for two simple reasons: 1. Information is power, and; 2. Timing is everything. Business users have frequently struggled to get the information they need to make decisions in a timely manner. More often than not, the bottleneck is their own IT department, which, by no fault of its own, fails to keep up with the continuous flow of queries, resulting in report delivery delays.

To that point, the rapid growth of self-service BI is largely a response to stretched IT staffs that were often unable to keep up with the incessant demand for new reports using traditional BI. According to preliminary research conducted for The 2021 Benchmark Report on Self-Service Business Intelligence, scheduled to publish in Q1, 42% of business users generally had to wait “too long” for IT resources to fulfill their requests for new reports. The wait time for a report was often several days or even weeks, by which time the information may have been stale or the opportunity to act upon it may have passed. Who are these business users? They are the consumers of the information. These individuals range from middle managers all the way up to the executive suite. They cut across functional areas, from marketing, market research and sales to finance, operations, competitive intelligence and new product development.

They also vary in terms of their usage requirements and level of BI sophistication, from what can be called casual users (individuals who require only periodic reports, with limited need to run their own custom queries or manipulate the data to generate additional insights) to power users (individuals whose day-to-day activities largely revolve around ad hoc data reporting and analysis, even to the point of obsession). Regardless of role or responsibility, the success of these business users, as well as the success of their companies, lies in their ability to access information in real time to drive continuous decision-making cycles.

 

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