Business Analytics

Introduction to Business Analytics

The word analytics has come into the foreground in last decade or so. The proliferation of the internet and information technology has made analytics very relevant in the current age. Analytics is a field which combines data, information technology, statistical analysis, quantitative methods and computer-based models into one.

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Data Scientist, Emphasis on Analytics

Data Analytical scientist deal with math, statistics, understanding the trends, solving the complicated data models etc. A major task in the job is the data mining and analyzing of the data extracted.

Quantitative Analyst / Modeler

A quantitative analyst/modeler helps in understanding the data models to support the organization in taking the major decisions in the organization. Quantitative analysts generally belong to the financial industry where the analysts need to undertake and manage risky situations and decisions.

Business Analyst

Business Analyst or the Data analyst need to build up the visual representations of the data and provide appropriate information to decision makers in the organization. A business analyst works on different tools and techniques to understand complex data models.

Business Analyst (Manager / Consultant)

A Business Analyst Manager should have the knowledge of technical tools, data analytics foundation methods, data gathering and processing which ensures appropriate analysis of the data models. Good communication skills, leadership qualities, strategic thinking are the major skills required for a Business Analyst Manager or consultant.

Pricing and Revenue Analyst

A revenue analyst’s primary job is to analyse a company’s finances. Their insights on financial data will help boost revenue growth.

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Difference Between Data Science vs Business Analytics

Both Data Science and Business Analytics involve data gathering, modeling and insight gathering. The difference between the two is that Business Analytics is specific to business-related problems like cost, profit, etc. whereas Data Science answers questions like the influence of geography, seasonal factors and customer preferences on the business. In short, Data Science is larger or super set of the two. Data Science combines data with algorithm building and technology to answer a range of questions. Recently Machine Learning and Artificial Intelligence have been doing their rounds and are set to take Data Science to the next level. Business Analytics, on the other hand, is the analysis of company data with statistical concepts to get solutions and insights.

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WHY OR WHY NOT BUSINESS ANALYTICS

3 specific types of business analytics

Descriptive Analytics – The one which tracks KPIs (Key Performance Indicators) to understand the current state of a business.
Predictive Analytics – The one which analyses the data trend to access the possibilities of future outcomes.
Prescriptive Analytics – The one which used the past performance data to generate recommendations to handle similar situations in the future.

Helps you monitor the progress of your mission – Quantified values and data help the business improve their analytical process by evaluating the data to gain a clearer picture of what to expect from the employees.
Helps increase efficiency – Business analytics can gather a large amount of data at a fast rate and display it in a formulated and appealing way to help achieve specific organizational goals.

Lack of alignment, availability and trust – In most organizations, the analysts are organized according to the business domains.
Lack of Commitment – Since the solutions that are prefabricated from the analysts are not particularly difficult to implement; they can be very costly and the ROI is not immediate.
Low quality of underlying transactional data

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SALARY AFTER BUSINESS ANALYTICS COURSES

Masters In Business Analytics Students Can Expect A $60,000 Average Salary After Graduation

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