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Business Analytics is a systematic and methodical presentation of data of any organization which is driven out of statistical and numerical analysis. Business analytics is a method which is used by the majority of companies today in order to make decision making effective and efficient. Thus, Business analytics course is a course which helps the students to learn the need and use of business analytics. Business Analytics serves as a systematic process which is a combination of data analytics and Business Intelligence on the basis of which companies rely on their process of management, I.e. Business Analytics is a continuous process which involves collection, processing and analysing the business data and operations, and with the help of statistical models and ideologies, transforming the outcome into business insights.

GIDAR is an Analytics Method that ensures systematic Business Impact. Why do we still struggle to make sense of the enormous amount of data available in the information era? GIDAR Analysis method addresses these points for you to avoid the Big Data hype trap. By setting up SMART Goals, applying a step by step process and using change management techniques, you will move from meaningless Reports to Results. GIDAR offers an easy yet powerful tool called the GIDAR Analytics Canvas that ensures that Information and Data translate into Change and Results.

I am an undergraduate (or any other) student & want to pursue career in Analytics, what should I do? I want to build a career / shift my career in Business Analytics, how should I go about doing so? Further, I receive multiple queries through mail / social media / comments asking the same. In order to make sure these queries are addressed in best possible manner, I thought it's best to write an article on this and provide a starting platform for everyone. While the subject itself is wide, I'll provide an overview of various things which can be done and focus on specific sub-topics through additional posts later on.

Easier to read and understand than expected (coming from someone who doesn't have a data analytics background). The author uses examples of major companies to help understand how businesses are applying data analytics.