Business Intelligence vs Business Analytics: What’s the Difference?

What is business intelligence?

Business intelligence is the process of collecting, storing and analysing data from business operations. BI provides comprehensive business metrics in near-real time to support better decision making. With better business intelligence, you can create performance benchmarks, spot market trends, increase compliance and improve almost every aspect of your business. Learn more about business intelligence and why it matters to your business.

Business analytics vs data analytics

Business analytics (BA) refers to the practice of using your company’s data to anticipate trends and outcomes. BA includes data mining, statistical analysis and predictive modelling that help make more informed decisions.

Data analytics is the technical process of mining data, cleaning data, transforming data and building the systems to manage data. Data analytics takes large quantities of data to find trends and solve problems. Data analytics is used across disciplines – from government to science. It’s not just confined to business applications.

The difference between business analytics and data analytics is a little more subtle, and these terms are often used interchangeably in business, especially in relation to business intelligence.

Data analytics is a broad umbrella for finding insights in data

Data analytics can refer to any form of analysis of data – whether in a spreadsheet, database or app – where the intent is to uncover trends, identify anomalies or measure performance. Additional mathematics or IT skills can help data analysts do everything from managing a database of subscribers to calculating yields for a potential investment.

Business analytics focuses on identifying operational insights

Business analytics focuses on the overall function and day-to-day operation of the business. A business analyst would deal less with the technical aspects of analysis and more with the practical applications of data insights. Some job responsibilities might include creating a streamlined workflow or choosing the best vendors.

Applying BA and data analytics in the real world

Let’s return to our online jewellery store example. A data analyst would look at how people are using your website, identifying trends in traffic, analysing visitor demographics and maybe even creating a system for tracking how customers click through different pages. A business analyst would deal more with the practical applications of this data and how it helps you make decisions for purchasing ads, creating new products and updating your website.

Clearly, all of these processes use data to improve your business, but let’s push a little further to understand the nuances between each.

Business intelligence vs. business analytics

The major difference between business intelligence and business analytics is the questions they answer. Business intelligence focuses on descriptive analytics BI prioritises descriptive analytics, which provides a summary of historical and present data to show what has happened or what is currently happening. BI answers the questions “what” and “how” so you can replicate what works and change what does not. Business analytics focuses on predictive analytics BA, however, prioritises predictive analytics, which uses data mining, modelling and machine learning to determine the likelihood of future outcomes. BA answers the question “why” so it can make more educated predictions about what will happen. With BA, you can anticipate developments and make the changes necessary to succeed. Applying BI and BA in the real world Let’s illustrate these differences with real-world applications of BI and BA. In this example, you sell home-made jewellery through an online store. Business intelligence provides helpful reports on the past and current state of your business. BI tells you that sales of your blue feather earrings have spiked in the north-west in the past three weeks. As a result, you decide to make more blue feather earrings to keep up with demand. Business analytics asks, “Why did sales of blue feather earrings spike in the north-west?” By mining your website data, you learn that a majority of traffic has come from a post by a Manchester fashion blogger who wore your earrings. This insight helps you decide to send complimentary earrings to a few other prominent fashion bloggers throughout the country. You use the previous sales information to anticipate how many earrings you will need to make and how many supplies you would need to order to keep up with demand if the bloggers were to post about the earrings.

Determine your business intelligence and analytics needs

Trying to decide if business intelligence or business analytics is better is not a helpful way to look at data management. In reality, a business needs both business intelligence and business analytics – descriptive and predictive analytics – to succeed. Plus, people throughout the business world often use these terms to mean a variety of things, so when choosing the type of platform, tools and talent you want to invest in, you should focus less on BI vs BA and more on what you need the data system to do and who will be using it.

Developing a business intelligence strategy is an important first step in implementing a BI solution. Ask important questions, such as:

• Who are the key stakeholders? Who will be using this system?
• What departments need business intelligence and what will be measured?
• What support do content authors and information consumers need?

Start using data to drive transformation in your business with Tableau Blueprint.