Many organisations rely on data to inform their decision-making spanning from their operations to overall business strategy. Making the right decisions will ensure you have a competitive edge and set you up for long-term success. Businesses can analyse their data through two primary ways – a traditional business intelligence platform or a data discovery tool. While both methods have their advantages, it is important to understand the benefits and limits of each when deciding which method is the right fit for your business. We explore both these methods below.

What is Traditional Business Intelligence?

At a basic level, business intelligence (BI) refers to a variety of processes, methodologies and technologies used to interpret an organisation’s raw data. It is used to support evidence-based decision-making. There are several related activities, including:

  • Online analytical processing;
  • Data mining; and
  • Querying and reporting.

By facilitating querying, businesses can ask data related questions and obtain answers. Traditionally, this involves developing an enterprise data warehouse and cubes that the business would use for reporting and analysis.

Two key examples include Enterprise Resource Planning (ERP) and Customer Relationship Management (CRM). An ERP is business management software that enables businesses to use, store and analyse data for a range of business activities, including human resources, manufacturing and, sales and operational planning.

A CRM is a technology used to manage and analyse customer interactions with the aim of improving the experience of the client within the organisation.

What is Data Discovery?

In contrast to traditional business intelligence, a data discovery tool is more time effective, as you do not need to integrate data into an enterprise data warehouse before you analyse it.

Data discovery is best understood as a business intelligence architecture that creates data using multiple sources. By integrating different data sources, it helps organisations discover hidden patterns and trends. It is particularly helpful when deciding how to improve business processes and identifying business opportunities.

What’s the Difference?

The key differences between traditional business intelligence and data discovery can be summarised as follows:

  • Business intelligence is best for answering questions about existing knowledge. For example, the number of product sales in the previous month. Data discovery can be used to uncover trends, which is often useful for making predictions. For example, the number of product sales likely to be sold in the coming month based on the previous data.
  • A business intelligence system takes months to build due to the need for an enterprise data warehouse. You can build a data discovery tool within a few days.
  • There can be different versions of truths when integrating multiple data sources through a data discovery tool. A business intelligence platform will only have one version of the truth.
  • A business intelligence system provides a broader and more detailed view into the processes and strategies of an aspect of the organisation. Data discovery is best for answering one-off questions for data with a short self-life.

Key Takeaways

Data discovery is not a direct replacement for traditional business intelligence. Each has their benefits, and an organisation can employ them based on the circumstances and needs at the time. In our next article, we will explore the circumstances where a business is required to produce their data discovery and metadata, particularly when the business stores it overseas.

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