The importance of data in an enterprise has never been greater. However, creating quality reports is a time-consuming process and the process has become more difficult in recent years as businesses have more data to review. A Boston Consulting Group study reveals that 40 percent of the time spent by managers is for writing reports. According to Harvard Business Review, 99 percent of the data is not even used or analyzed. This is where business intelligence (BI) comes in: BI is often used to describe various tools that provide quick, easy-to-understand information about an organization’s current situation, based on data that is readily accessible.
Today, we’re in the midst of a BI revolution and going digital has become a necessary imperative for businesses today.
Consolidating technology shifts
The dawn of the new millennium led to BI platforms creating products based on the dominant architecture of the time. More users meant more files, so high-performance desktop computers with single-processor server systems with more memory and directly connected storage were purchased.
The design point for the first two iterations was a data-centric stack, while the third generation is heading toward a network-centric stack. Critical technological changes began to emerge as mega-vendors like IBM and Oracle were busy consolidating. This led to new technology shifts. BI solutions were previously often deployed on the laptop, and business software offerings were difficult to distribute globally. However, when the web became the focal point of design, a completely web-based architecture was developed, with a quick installation process and faster implementation options.
An article by Forbes highlights that before decisions are taken, data visualization is the “last mile” of the analytics process. Traditionally, computers and humans communicate by visualization, which takes the form of graphs, maps, and dashboards that illustrate key observations and assist us in determining what the data suggests should be accomplished.
Reports and dashboards were the fulcrum on which previous BI solutions relied upon.
However, as architectures changed, so did the functionality of BI solutions. A professional individual might claim that a specific collection of data has provided self-evident insights. However, the audience must be able to comprehend the ideas in the same way. By using analytical logic, telling stories by data will help close the void. A dashboard can only provide users with graphical insights or tables that they do not completely comprehend. To explain the true sense of the results, strategies were developed that included storytelling tools.
The art of combining hard data with human communication to create an entertaining storyline based on reality is known as data storytelling. It employs data analysis tools (such as maps and images) to help the viewer understand the significance of the data in a convincing and meaningful manner.
Smart Data Discovery
Smart data exploration, also known as augmented intelligence, is increasingly setting the stage for the next major change in the analytics environment. “By 2021, the number of users of modern BI and analytics systems who are distinguished by smart data discovery capabilities will rise at twice the pace of those that are not, and will offer double the market value,” according to Gartner’s study on ‘Critical Capabilities for BI and Analytics Platforms.’
The road ahead
A recent Accenture study reveals that companies will go extinct and lose to their competition if they do not embrace big data, as per 79% of the executives surveyed. End-users on modern BI networks are supposed to be extremely scalable. A modern BI server should be capable of concurrently providing reports and analysis to hundreds or thousands of users. With no extra charge, the modern BI platform should be taking full advantage of today’s network-centric stack.