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What is Business Intelligence?

by YOSS Community Writer, on June 27, 2019 at 7:00 AM

Business intelligence (BI) is a collection of tools and procedures used to collect and analyze the data that businesses accumulate. Its purpose is to provide people throughout the business with ways to extract useful information from large collections of data.

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Most business professionals have had the experience of manually performing data analysis in a spreadsheet. The thing is, this process is inefficient and often costly. With BI, people can extract actionable information from business data without wasting time or making errors.

The History of Business Intelligence

The term "business intelligence" dates back to the 1865 publication of Richard Millar Devens' Cyclopædia of Commercial and Business Anecdotes. However, its usage at that time referred to knowledge about the business environment. It wasn't until much later that we saw a modern take on the term.

The most important event in the history of BI occurred in 1958 when HP Luhn published A Business Intelligence System in IBM Journal. As a result of his work, IBM created some of the first BI tools.

In the 1970s, BI became more flexible with integrated data warehouses and techniques that made data uniform and thus more usable. It wasn't until the 1990s, however, that large corporations began using BI.

And in the 2000s, BI became more widely used than ever. This is when self-service analytics came along. Individuals can use these analytical tools to work with the centrally located data, and this process represents where BI is today.

Business Intelligence Processes

BI works on a self-serve basis where you have various tools for analyzing data. It isn't categorically different from the way data is traditionally analyzed, and the biggest difference is the way that the data are processed and stored.

Businesses are constantly collecting data. In a BI environment, this data is sent to the IT department for storage in a data warehouse. Once in the data warehouse, the data is cleaned and formatted so that it can be stored consistently in databases for use by others in the business.

The tools used to access the data may be a collection of different BI tools that were created onsite, provided by a third-party, or both. And they’re more commonly integrated into a single dashboard like SAP BusinessObjects.

There are a number of ways that the data can be used:

  • Reporting and Querying: Extracting information and presenting summaries.
  • Data mining: Finding patterns and other information in large data sets.
  • Descriptive analytics: Determining why changes in data happened.
  • Benchmarking: Comparing the business' performance to other businesses in the same industry.
  • Process analysis: Studying business processes to find ways to improve.
  • Data visualization: Presenting large data sets in ways that are easy to understand.
  • Predictive analytics: Processing data to predict future trends.

Business Intelligence vs Business Analytics

BI is often confused with business analytics (BA). In fact, some experts disagree about what the differences are. For example, SAP BI advocate Timo Elliott has said, "What’s the difference between Business Analytics and Business Intelligence? The correct answer is: everybody has an opinion, but nobody knows, and you shouldn’t care."

There is a general agreement, however, that BA is predictive. BI is interested in what data explains about the past and present, and BA is interested in what it can tell us about the future.

It is best to think about BA as being a part of BI. One of the most important aspects of BI is setting up the process of taking business data and making it available to the entire enterprise. After that, there are the many tools that allow you to interact with and analyze that data.

It is only after this that BA comes into play, because it allows you to make data-based decisions about the future. As part of this, BI is increasingly being used with machine learning to automate that process.

Business Intelligence Tools

SelectHub surveyed more than 600 businesses about what BI tools they wanted to use. They collected data on some of the same items we discussed above (visualizations, reporting, data mining) as well as the following:

  • Dashboards: Interfacing to data with personalized views.
  • Predictive analytics: Processing data to predict future trends.
  • ETL (Extract, Transform, and Load): Extracting data, processing it, and saving it.
  • OLAP (OnLine Analytical Processing): Querying, data mining, and reporting.
  • Drill down: Viewing data at a smaller and smaller level (e.g., global sales, national sales, regional sales, etc).

The results show:

Type Wanted
Dashboards 89%
Visualizations 83%
Reporting 48%
Predictive Analytics 42%
Data Mining 34%
ETL 21%
OLAP 16%
Drill Down 11%


These tools are available from a wide variety of companies including SAP, Microsoft, Oracle, Qlik, and IBM.

(Note on the above table: It could also displayed as a bar graph.)

Examples of Business Intelligence

A couple of examples will help solidify how BI helps companies.

Napier Brown

Napier Brown is a sugar distributor. They developed a number of sales analytics spreadsheets that allowed them to determine their margins by customer, product, and week. There were many problems. For example, there was no way to drill-down to the base data at the invoice level. Also, because all this data existed in spreadsheets, it wasn't necessarily consistent or up-to-date.

Napier had Matillion set up a BI system for them. This not only solved their problems with data access and reliability but it also greatly cut back on the amount of time that their people needed to create reports.

HelloFresh

The meal-kit company HelloFresh does a lot of online, regionally-focused marketing. They were using Google Analytics and internal production data in MySQL databases to manage their approach, with Excel spreadsheets as their interface.

This did not allow the company to react in real-time as they needed to. They contracted with Tableau who set up ETL processes so that the data was up-to-date and available from a single source. This allowed HelloFresh to make marketing decisions with near-real-time data while saving them up to 20 worker-hours per day.

Summary

BI greatly improves the power of business data and the amount of time your people need to work with it. If you are looking at introducing BI to your operation, YOSS has many analysts and consultants who can help you out. Sign up with us now.

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