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A Beginner’s Guide to Business Analytics

October 12th, 2017 by admin | Filed under travel-news.
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A company wants to launch a new product in the market, what does it need other than a great product is the data to back its every decision, to make the product successful and profitable in the market.

According to techtarget.com

Business analytics is the practice of iterative, methodical exploration of an organization’s data, with an emphasis on statistical analysis. It is used by companies committed to data-driven decision-making.

The aim of analytics is to process large data set of the company and help in the decision-making process.

Business analytics is one of the most important domains of any business in the world. it has become an inseparable tool which is defining the growth strategy of a company.

Business analytics begins with a data set (a simple collection of data or a data file) or commonly with a database (a collection of data files that contain information on people, locations, and so on).

The data has become the most important asset of a company and they are utilizing their resources to find the meaningful information and key insights which benefit their company directly.

Types Of Business Analytics:

Descriptive Analytics:

This describes the current state of a company by tracking key metrics and determines trends from the current dataset.The aim of this type of analytics to determine what has happened.

it provides primary data processing method to proceed further.

It also analyses how the data looks like currently and identifies future behavior.

For ex. a location bar chart for a travel company which wants to target customers by location.

Predictive Analytics:

It is the most important and advanced analytics which creates models for the prediction of a particular event or performance of a particular product by using historical and current data sets.

it is generally an area of data scientist and data analysts who build predictive data models using the advanced algorithm, regression analysis, time series analysis, decision tree.

It has become more important with big data and financial companies have been the prominent user of it, to determine events before they occur.

Example: Multiple regression is used to show the relationship (or lack of relationship) between age, weight, and exercise on diet food sales.

Prescriptive Analytics:

It determines the best solution for a particular problem when the different set of solutions are presented.

It also provides decision options by processing new data to improve the accuracy of predictions and decision options.It is the mix of data science and management science which provides the best route possible for a particular path.

Example: A sports store has a limited marketing budget to target customers.

Application and Uses:

It provides insights into the key decisions of the company in various domains which help the company to gain an advantage over its competitor.

• It leverages the analytics to generate more profit for the company and improve its performance.

• Businesses all over have been using it to determine and improve their optimal resource allocation, supply chain optimization, inventory management, employee performance, project Completion rate, Skill Map, Improve their Product portfolio etc.

• Two key areas are Business Intelligence and Statistical Analysis.

• In statistical analysis, the statistical algorithm is applied on data to predict the performance of a service or a product.

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