Big Data vs Business Intelligence

Last month we introduced the Internet of Things (IoT) and why businesses big and small are using these internet connected devices to collect big data related to their businesses.



The term “Big Data” is often used interchangeably with the term “Business Intelligence” but these are two entirely different things. “What is the difference between ‘Big Data’ and ‘Business Intelligence,’” you may be wondering, and “how does this apply to my business?”  This article explains.


What is the Difference between “Big Data” and “Business Intelligence”?


Big Data Consultant Eric Brown offers this succinct explanation: Business Intelligence helps find answers to questions you know. Big Data helps you find the questions you don’t know you want to ask.


Regardless of how technically sophisticated your business is (or isn’t), you are surrounded by big data. Every time you collect information about your customers, prospective customers, vendors, etc. you are collecting big data. You may be collecting business information in structured form, which is the data contained within organized databases that is easily searchable (like data found in Customer Relationship Management Software, for example). Most of your data, however, is unstructured (or unorganized). Up to 80% of a business’ pertinent data is in unstructured forms like emails, Microsoft Office files, paper files, etc.  Imagine what might be uncovered if your organization’s unstructured business information was managed in a way that made it easy to mine and interpret.


This is where Business Intelligence comes in.  Business Intelligence is a tool that helps organizations track, process, store, and analyze its structured and unstructured data in a way that enables decision makers to gain access to information about their business. Maybe you are a marketing professional seeking to measure the performance of marketing campaigns, a sales professional seeking to better forecast your pipeline or an operations manager seeking insights on production activities. These are all examples of Business Intelligence Projects. Regardless of the project, the process starts with the question, “what do I want to know?”


Meet Bob, Bar Owner + Technophobe


Three years ago Bob bought a bar. His first priority was increasing the bar’s number of regular customers to boost sales. Bob knew that tracking, analyzing and understanding his sales and inventory was critical to the achievement of this goal, but he shared a common trait with many other small business owners: he was challenged to use the data he already had to make informed business decisions.


At the suggestion of his sister, Bob began maintaining a daily spreadsheet containing columns of information that reported the gross sales of each of his major product lines.  This information was collected for the first few months of ownership as Bob learned the business. At the end of the year, Bob struggled to make use of the spreadsheet. He could not gain insight from the clutter. Then his sister introduced him to Microsoft’s Power Pivot – a data modeling tool available within Microsoft Excel.



Bob used the data from his spreadsheet to graph the bar’s sales trends in a line chart. The visual representation of his chart data allowed him to easily identify dips and spikes in his sales across all product lines while eliminating the distraction caused by the large volume of data contained within his spreadsheet. He was able to see, at a glance, which products had the highest sales volume and which product lines he should consider dropping.  The Power Pivot tool allowed Bob to visually drill down into his sales by month, week and day. He was able to correlate a spike in sales the third week of September to a regional convention that takes place annually. In year two of his ownership he executed a marketing campaign called “Toast the Taxes” the Tuesday before tax day (a day he historically had low sales volume). Following that campaign, he saw a significant growth in sales that he can attribute to that marketing campaign.


Selecting a BI Tool


It used to be that Business Intelligence tools were only available for big businesses with dedicated data scientists and technicians responsible for maintaining and using them. This is no longer the case. The Power Pivot tool is an easy to use add-on to Microsoft Excel.  For the technically savvy user, Microsoft offers Power BI, a free to use service that provides advanced data exploration, shaping, modeling and report creation from multiple data sources including many popular cloud services like MailChimp or Salesforce CRM, content from Microsoft Office files, etc.


There are dozens of Business Intelligence tools ranging from basic to enterprise class (and ranging in price from free to thousands of dollars). Like any software, you must identify your goals, including the value of the insights to be gained from your data project. While the example provided here is rather simplistic in nature, most big data projects are far more complex. There are likely as many failed projects as there are successes.  Proper planning and use of the tools can help your business make the right decisions in the right time, cut costs, identify new business opportunities and improve performance but as with all IT projects, proper planning is key.

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