Business Analytics Training

With SAS, R and Hadoop Business Analytics Training in Chennai, you will be able to extract useful information from millions of bytes within minutes. This Business Analytics (BA) Training in Chennai program focuses on Forecasting, Econometrics and Time Series Analysis and prediction of future outcomes based on historical patterns. It makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management to drive decision making.
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Business Analytics Training In Chennai

Certified Business Analytics Training in Chennai. Get to know all about analytics, data science & careers in analytics from industry experts! Hands on 70 hours training on Live Business Analytics Project. The program consists of classroom training with a specially designed 10 days hands-on workshop where you can start interpreting data along with projects and assignments that have a real-world case study mode rather than just theory.

Business Analytics Training Course Syllabus in Chennai

• Foundation of Analytics
• Statistical Inference
• Applications of Analytics in Business Function
• Special Analytical Methods
• Information Management in Analytics
• Advanced Business Forecasting
• Advanced Analytics
• Application of Analytics in Business Verticals

Best Business Analytics Training in Chennai

This Business Analytics Training for data analysts new to SAS Enterprise Guide and SAS Enterprise Miner provides valuable experience using powerful statistical software to complete the kinds of business analytics common to most industries.
Analytics is the scientific process of deriving business insights from raw data to support decision making. Through this business analytics course you will learn how to use analytical techniques and the R language to solve business problems in a number of fields like financial services, retail, FMCG etc. This is a comprehensive course which will take you from the basics of statistical techniques and R language right up to building predictive models. By the end of this course you will be able to demonstrate your business analytics skills to employers.

Tools taught
R and Advanced Excel. R is fast emerging as the most popular tool.

Business Analytics training using Big Data, Hadoop and SAS

SAS support for big data implementations, including Hadoop, centers on a singular goal – helping you know more, faster, so you can make better decisions. Regardless of how you use the technology, every project should go through an iterative and continuous improvement cycle. And that includes data preparation and management, data visualization and exploration, analytical model development, model deployment and monitoring. So you can derive insights and quickly turn your big Hadoop data into bigger opportunities.

Business Analytics training with Popular analytic methods

There are three predominant flavors of analytics in use today.

• Descriptive statistics. Descriptive statistics have been around the longest. Remember the Swedes in 1749? Tabulating population counts was an early foray into descriptive analysis – the summary of collected data points. These are the models that will help you understand what happened and why. There are still plenty of descriptive analytics in use today – everything from how many clicks a page receives to how many units are produced vs. how many are sold.
• Predictive analytics. Predictive analytics has surged in popularity. The desire to predict customer behavior has been a main driver. Increased computing power with the ability to run hundreds or thousands of models quickly – and widespread adoption of predictive techniques like support vector machines, neural networks and random forests – are bringing predictive analysis to the forefront of many organizations. These models use past data and predictive algorithms to help you determine the probability of what will happen next. Learn more about predictive analytics.
  
• Prescriptive analytics. Prescriptive analytics is the newest kid on the block. Knowing what will happen and knowing what to do are two different things. Prescriptive analytics answers the question of what to do by providing information on optimal decisions based on the predicted future scenarios. The key to prescriptive analytics is being able to use big data, contextual data and lots of computing power to produce answers in real time.

About Business Analytics

• Business analytics focuses on developing new insights and understanding of business performance based on data and statistical methods.
• It makes extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling and fact-based management to drive decision making.
• It focus on Forecasting, Econometrics and Time Series â€" Analyze and predict future outcomes based on historical patterns

Benefits

• Learn to solve business problems using analytics in a variety of fields like retail, FMCG, financial services, telecom, etc.
• Provides training on the latest tools and techniques in the field of analytics.
• Hands-on learning on latest analytic tools
• Learning of Advanced predictive modeling techniques
• Program has been designed by industry experts

Objective

Business Analytics is a specialized course designed to deliver knowledge on application of statistical concepts in real world scenarios. This course is designed to equip professionals working in Finance, Marketing, Economist, Statistical, Mathematics, Computer Science, IT, Analytics, Marketing Research, or Commodity markets with the essential tools, techniques and skills to answer important business questions.

Participants will be able to:
• Explore data to find new patterns and relationships (data mining)
• Predict the relationship between different variables (predictive modeling, predictive analytics)
• Predict the probability of default and create customer Scorecards (Logistic Regression)

After completion of this program, the participants
• Understand a Problem in Business, Explore and Analyze the problem
• Solve business problems using analytics (in R) in different fields

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