Why business analytics is a force to reckon with?

Why business analytics is a force to reckon with?

What is business analytics? One might confuse it with data analytics, as they are intricately related. Business analytics concentrates on multiple aspects of a business. For instance, business analytics can help a business decide whether to upgrade the previous product or discontinue it in favour of making space for a new one. Unlike data analytics, the focus of business analytics is always on the business processes and how the data around it can be leveraged to drive progress.

Big data as a game changer

Big data has become a valuable tool in managing and planning many aspects of the business. Big data analysis allows a business to understand geographic, historical and seasonal aspects of a market and plan accordingly even before starting. And continues to help a business in subsequently understanding the mindset of consumers, and factoring in that knowledge in the pricing of the products, introduction or elimination of products etc.

But without the guidance of business analytics coordination between all the aspects of an operation will remain unsupportive and ineffective. Business analytics is more about what a business should do for enhancing its performance.

Drawing  a line between data analytics and business analytics

A data analyst can predict the numbers of clients that might be willing to seek service from a competitor and a business analyst helps to devise a strategy for prevention of the same.

Big data analysis and business analysis enables a company to launch a value for money product in the market, affordable and full of utility. Something that never fails to boost sales figures.

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Business analytics mostly deals with data of an organization. And involves descriptive,  predictive and prescriptive analysis of the data.

Three folds of analytics

Descriptive business analytics illustrate a given situation, a case or a market scenario based on available data. It deals with the organization’s standing in a given time and place. Using market and organizational data draws a picture depicting all the roles being played and all the ongoing activities.

Predictive business analytics is practically the next step of making sense of the available data by the use of machine learning and statistical methods. The goal is to predict the probable future and raise red flags for reasons of anxiety. It is however quite precarious in nature and can not be relied upon blindly. Predictive business analysts predict and deduce based on data generated in the past.

Prescriptive business analysis is the culmination of descriptive and predictive analysis. The job is to provide recommendations for a business regarding the aspect of concern.

These three kinds are however not necessarily performed in the given order, sometimes all three are not even relevant together. Business analytics can be used separately for all the different departments based on their needs.

The ideal workflow

After a data analyst reports a troubling change of patterns in last years’ sales figures, the business analyst gathers all the implications from different departmental data analysis and finds out the solution. Hence, a person in the role should possess the skill to view a business in a holistic manner. Statistical capabilities and deep business-related knowledge are essential for the role as well.

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The technicality of data gathering, handling and utilizing are not the areas of interest for a business analyst. Instead, a conceptual and pictorial set of conclusions can help in devising a new strategy. The role is defined by experience, skill and foresight capable of driving the business safely and steadily to its goals. Clearly, skills regarding marketing, finance sales and all other aspects of a business can prove to be an asset for an analyst.

A lot of work by data scientists, mining and analysing big data can go in vain without the guiding hand of business analysts. The demand for a business analytics course in Delhi has skyrocketed for good reasons.

By using machine learning and advanced prediction methods it complements the conclusions drawn by data scientists.

Data generated from various parts of operations are like dots in need of a connection, without proper business analytics it remains disconnected. Hence, only by big data analysis, it is impossible to predict and plan the actions safely. It needs the supplementation and complementation of business analysis for being of any use.

Data analytics empowers business analytics. There is no question of replacement of the later by the former as they perform best together. We can even take a step forward and say that business analytics is an extension of data analytics, that makes data work for businesses.

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