How the Implementation of Business Analytics Works


Analyzing data to improve business. That is probably the most straightforward and simplified way of describing business analytics. But there is much more to it than meets the eye at the first glance. In the course of this article we will try to walk through the basic workflow of business analytics. Before we start let us quickly familiarize ourselves with the main things which we are going to talk about.

Business analytics: What is it?

If you are an advanced reader, you can simply skip this part, unless of course, you want to brush up your acumen.

Business analytics is essentially a discipline which studies the analysis of data and its application towards improving business. In a way of seeing if you add the goal of influencing and improving business to the discipline of data analytics and make certain modifications to suit that purpose, it takes the form of business analytics. Whether data analytics is a subset of business analytics or the other way round is an argument which we do not want to get into.

Descriptive, Predictive and Prescriptive analysis

These terms are relevant to both the fields of business analyst and data science. These three types of data analysis are applied depending on the end goal of the endeavour, and each supports the other.

Descriptive analysis

This involves the gathering of structured or unstructured data from an enterprises own databases and analysing them to understand what has happened.

Predictive analysis

This uses predictive models to find out what may happen in the future if certain changes are made. This approach interprets the relation between historical data and the actions taken before the time of generation of that data and predicts the future outcomes with a certain amount of accuracy.

Prescriptive analysis

This approach uses data to make suggestions towards improving businesses. This approach has a lot of value added to it and it is also the most complicated one.

The three initial steps of business analytics

Locating the problem

The first step is to find a problem. The problem can be visible to the naked eye, for example, a severe fall in conversion rates after a certain update on the enterprise’s website, or it can be hidden under heaps of data, like if you find a mild downward gradient on the graph representing profits after the installation of a new fulfilment center. Some problems may require immediate redressive measures and some may occur as an irreversible downside of an otherwise profitable endeavour. The business analyst has to find these problems and arrange them according to priority. The problems may be regarding targeting the right group of customers, or opening up a bottleneck in the supply chain.

Chalking out a plan

This does not take a lot of time but it is as important as any other step. If you want to use analytics to address a certain problem you will have to identify certain data sources to tap into. The data can be clean and structured or very dirty and unstructured. Looking at these things will help you understand the efforts that might be involved in the endeavour and also the likelihood of success.

Preparing a business case

The line of analysis you want to pursue may involve a fair amount of money and you want the executives to know and like the plan. Creating a presentation that clearly states the problem, the likely solution, the budget and the chances of return of investment, can get you the necessary backing while keeping the managers in the loop.

Grab, clean, analyze, visualize

The sub-heading says it all. You need to procure the data, clean it up so that it can run on the analytical model smoothly, modify the analytical model according to the needs. After you have done all that, visualize the data to draw inferences and share them with the stakeholders.

That is pretty much it. However, there are other things that you need to know.

The quality of the data determines the quality of analysis. If you use garbage data your results will be useless too. The better part of the data will be unclean and difficult to handle - cleaning the data will probably take the maximum amount of time, so be patient.

The volume data has increased manifold over the years and traditional tools are falling short of the required efficiency by far - big data is the key.

You are likely to handle more unstructured data than you may be prepared for. You will need to improvise and use the best of your abilities to get through. So, make sure you train well. A business analytics course in Bangalore can help you prepare for the task. This city has the best courses on offer.
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