Smarter Businesses

Data Collection

Have you ever wondered how businesses get so good at pushing our buttons? Every now and then, I keep receiving product promotions or limited-time sales on things that interest me as a buyer/ consumer. Most of the time these emails would urge me to buy, even though I’m aware that it’s a want, not a need. But how? I don’t recall answering a survey about my shopping list. How was this possible? These days, businesses have become very competitive that they’ve adopted intelligence systems that help them collect data, analyze it, predict market trends. According to Chen et al. (2012), business intelligence and business analytics, along with the related field of big data analytics have become increasingly important in both academic and business communities over the past two decades.

Business Intelligence, Business Analytics, & Big Data

Business Intelligence (BI) is defined as a set of tools or systems that help in organizational strategic planning processes. It is about delivering relevant and reliable information to the right people at the right time, with the goal of achieving better decisions faster (Hitachi Solutions Canada, 2014). Business intelligence deals with situations where questions such as what occurred, how many, how often, where, the root of the problem, and what actions are required occurs.

Business Analytics (BA) on the other hand, refers to the skills, technologies, applications, and practices for iterative exploration and investigation of past business data to gain insight and drive business planning (Weinschenk, 2013). It involves using tools and techniques to turn data into meaningful business insights. Such data could be from several sources including spreadsheets, databases, social media platforms, and others. Business analytics commonly investigates what is currently happening, what is expected to happen if a certain trend continues, and what will be the possible outcome.

In relation to both business intelligence and business analytics, big data is the term used to represent the vast amounts of data sets that are collected and analyzed computationally to determine patterns, trends, and associations. The more data collected, the more difficult it becomes to analyze and predict outcomes. However, with the use of BI and BA, it becomes extremely quick and efficient.


Imagine you are the manager of an electronics brand that has both multiple stores and online shops. To keep track of your sales and customers, you set up customer loyalty cards, which customers swipe in the store every time they make a purchase or login into their online accounts when purchasing online. By using loyalty cards, information about a customer’s purchase, whether in store or online, are collected and stored in the company’s databases. Think of this as data being collected, which results in big data. Then using BI and BA, you as the manager can now generate reports, analyze sales, and determine which customers are loyal to your brand, what they usually buy, and which store do they prefer to buy from. You could also predict whether customers prefer to shop online or in store. This enables you as the manager of your business to predict needs, preferences, and habits of your customers so you can forecast and predict new sales opportunities, better customer services, or target market campaigns. On the business’s perspective, this educates the business as a team, providing the necessary skills and experiences based on techniques to delivering quality customer services. Here is a classic example showing the future of shopping involving the uses of big data, business intelligence, and analytics.



Chen, H., Chiang, R. H. L., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188

Hitachi Solutions Canada. (2014, January 26). What is business intelligence [Video File]. YouTube. Retrieved from

Weinschenk, V. (2013, September 8). Business Intelligence and Business Analytics Defined [Video file]. YouTube. Retrieved from



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