Data Explosion to Real-Time Cloud Analytics

Business Intelligence History

This is part of Solutions Review’s Premium Content Series, a collection of contributed columns written by industry experts in maturing software categories. In this submission, GoodData CEO Roman Stanek offers a quick lesson on business intelligence history: past, present, and future.

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A new year is a time for reflection. We spent 2021 asking industry professionals and enterprise leaders how their business intelligence (BI) capabilities have shifted in recent years, and the overwhelming response was that BI has grown to be the key to their company’s success. In fact, according to the recently published Cloud Computing and Business Intelligence Market Study by Dresner Advisory Services, a majority (54%) of enterprises say cloud BI is critical to their current and future strategies.

Modern BI has exploded in popularity because it promises to make sense of the tsunami of data that every business is dealing with, as well as uncover the insights within that are vital to winning in the marketplace thereafter.

Since the digital revolution, also known as the introduction of technological services into the business world, companies must decide how to use company data in the best possible way and move their business forward.

Business Intelligence History

The First Usage of BI

I initially stumbled upon the term business intelligence in the Encyclopedia of Commercial and Business Anecdotes. Published in 1865, the book describes BI as when a business owner profits from information by actively gathering and acting on it before their competition. Even in a pre-digital world, businesses knew the importance of gaining actionable information and using it to improve their products and services.

Before BI, it was commonplace to change the course of your company based on impulse and anecdotal evidence. The concept of BI was the first instance of attributing business success to the awareness and usage of empirical data rather than simply personal instinct. Business leaders soon realized that making decisions about your organization without qualifying data is like uprooting your family to a new town without a job, home, and community in place — the baseless risk is astronomical.

With the introduction of BI also came a shift in business operations and expectations on how one should run a successful company. As the world adapted to the start of the digital revolution, BI advanced decision-making grew past internal corporate awareness and into data visualization and cloud computing.

BI Within the Context of a Digital Revolution

As computer technology and the use of machine learning grew in prevalence, data-driven decision-making became deeply rooted in successful companies beyond upper management and managerial levels.

The first generation of BI software was largely managed by the IT department, which acted as the singular guardian of all enterprise data. Once stored, data was normalized — removing redundancy and duplication — to make it easier to run queries and retrieve data for reporting. Ultimately, the IT organization would deliver a static report to the business owner.

Given these drawbacks, this approach was soon eclipsed by a more agile approach that favored self-service capabilities. A new set of BI products emerged that eliminated the technical stack solely designed for data experts, and focused on providing data discovery and visualization tools to business users. Thus, cloud computing and data visualization was born.

Present Day

Today, cloud computing serves as a repository for both structured and unstructured data, which creates an ideal platform to provide BI applications with data gathered from a whole range of devices, no matter time or location. Because of this, the flexibility and scalability of the cloud act as an ideal complement to BI activities. Business users are empowered to use BI tools to access their data — even without advanced technical skills — since the data insights can be displayed and interacted with in an easy-to-use manner.

This evolution has democratized data and greatly accelerated the speed of data analysis; companies can make data-driven decisions more quickly and keep up with competitive environments. Plus, now that enterprises are increasingly migrating their data to the cloud, companies can enjoy data visualization and analytical benefits such as lowered cost, increased deployment speed, and ease of use — all within the cloud.

Cloud-based BI has the potential to become a lynchpin in the analytics and BI strategies of enterprises — including self-service BI — by providing end-users with real-time access to business-critical data that comes with the addition of the cloud. Now, companies are even embracing cloud-native computing, or headless BI, which is the concept of building and running applications to take advantage of the distributed computing offered by the cloud delivery model. This decreases costs, improves efficiency, and enables real-time analytics by reducing latency.

Being able to apply analytical reasoning to data through interactive visual interfaces has revolutionized the BI industry. Now, analytics companies can grow BI not only by making the analytical process easier than ever but also by allowing anyone within the organization to gain valuable insights from the company data, regardless of technical knowledge.

The Future: What’s Next for BI?

Ultimately, scaling BI within your organization is a critical step in becoming a data-driven organization. Humanity now lives in the information age, and BI is a crucial feature of our time that works to make sense of it all.

Prioritizing the accessibility of data — and improving the way companies deliver and design that data through methods such as composability and a modern data stack — are necessary to keep up with the ebb and flow of the enterprise market. Allow your organization to be agile within the space. For example, over the years, GoodData’s branding has evolved alongside changes in the industry and subsequent shifts in internal priorities. From traditional BI to self-service BI to augmented analytics, this flexibility and know-how regarding the next best tactic to thrust your organization ahead of its competition are at the core of business intelligence.

Roman Stanek
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