Difference Between Business Intelligence and Data Analytics


Using the data from the past, business intelligence helps you in decision making by leveraging different techniques. BI is a broad term that involves three steps:

1) Data mining

2) Data analytics

3) Big data

The CEO and the founder of Big Data Startups, Mark van Rijmenam says that "the difference between Business Intelligence and Data Analytics lies in the fact that Business Intelligence helps in making business decisions based on past results while data analytics helps in making predictions that are going to help you in the future."

How data analytics contribute to the business world:

We are living in a time where everything is driven by data, and with every second that passes by and every child that is born more and more data will be produced. And it's very important that we learn how to manage that interpret this data so we can it can be used to study the past and form a future.

The business world is now adopting this perspective and uses the techniques of data analytics to go about their way. From the beginning of a startup to its growth and transformation into a large profitable company, the usage of the knowledge of data analytics is extremely important.

Keeping the company operates and its daily operations running smoothly without any delay is the major goal of any company. Without efficiency in its way of operating a company would soon seize to exist. Any company can become more efficient simply by applying the logics data analytics to its data. Once your data has been analytically deciphered, you can remove all the inefficiencies and the risk factors. This way, your company's revenue will surely increase. You can also pinpoint to all those factors where a company is lacking.

You can also use this technique to know whether your company's logistical department is spending extra or less. Then you can implement this knowledge to make changes in the future. In the same way, you can also evaluate the financial and accounting operations and make them more efficient.

A business can now take larger risks with more confidence because they are flexible enough to adjust to the risk factors at any stage which can be easily obtained through data analytics. As the company now knows which risks are worth taking and which are not, they are likely to grow economically.

Also Check : Data Analytics and Marketing


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