Almost every organisation is grappling with three major types of Business Intelligence. These types represent the changing needs of business and the insatiable demand for insights.
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What are the three types of BI?
The first generation of business intelligence software was dominated by the IT department, which served as the central guardian of enterprise data.
The Extract, Transform, Load (ETL) process was used to combine data from various sources into a single database or warehouse, which was then normalized to eliminate redundancy and duplication. Business users, who lacked query language expertise, relied on IT staff to perform queries and generate static reports, which often took days or even weeks to complete.
Time is money
However, a new set of BI products emerged that focused on providing self-service data discovery and visualization tools to business users. This empowered business analysts to conduct ad-hoc analyses of multiple data sources, exposing hidden patterns and outliers. This revolution democratized data and accelerated the speed of data analysis, leading to data-driven decisions in competitive environments.
As data sets grow, data preparation requires skilled users to make sense of large data sets, which can be overwhelming for employees. The chronic shortage of analytics skills has led to the emergence of a third approach to BI, called Augmented Analytics, which automates insight generation using machine learning and AI algorithms. Many BI platforms have built-in capabilities to automate data preparation and detect correlations and anomalies in large data sets. However, there is still considerable hype surrounding this approach.
The three ages of BI have evolved from pixel-perfect reporting engines to AI-powered analytics platforms.
The traditional BI was owned and managed by IT, with limited self-service capabilities and a focus on reporting and KPIs. Modern, self-service BI is driven by business users and provides some autonomy for data analysis, with a focus on ease of use for non-technical users. Augmented Analytics does not require IT assistance for defining data models, with AI automation significantly increasing ease of use. Data correlation and insights are automatically generated to drive decision-making.
In practice, most organisations will combine elements of each type.
Overview of Traditional, Modern, and Emerging BI
Business Intelligence (BI) has come a long way since its inception.
There are now three major types of BI: Traditional, Modern, and Emerging BI.
Each type has its own set of features and capabilities.
Traditional BI systems are designed to handle structured data, process data in batches, rely on reports to communicate insights to decision-makers, and are IT-dependent.
On the other hand, Modern BI systems are designed to be self-service, provide real-time insights, offer interactive dashboards, and are mobile-friendly.
Emerging BI systems are incorporating artificial intelligence, natural language processing, predictive analytics, and advanced data visualization techniques, and are increasingly cloud-based.
To learn more about each type of BI and its unique features, check out our Overview of Traditional, Modern, and Emerging BI
Key Features of Each Type of BI
Each type of BI has its own set of features that cater to different business needs.
Traditional BI systems are designed to handle structured data and rely on reports, while Modern BI systems are designed to be self-service and provide real-time insights.
Emerging BI systems are incorporating artificial intelligence, natural language processing, predictive analytics, and advanced data visualization techniques, and are cloud-based.
Learn more about the Key Features of Each Type of BI with our in-depth look at the unique features of each type of BI and how they can benefit businesses of all sizes.
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