Introduction:

Data analysis is an essential component of data mining and business intelligence (BI). It is essential to gain the insight that drives business decisions. Enterprises analyze data from multiple sources using large data management solutions and customer experience management solutions that use data analysis to convert data into scalable visions For implementation, dealing with complex data sets for deeper insights and better decisions, this advanced analytical course will provide you with a definition of predictive analytics techniques so you can formulate strategic and operational questions including marketing and finance Operations or other business applications in the real world.

In this course, you will cover a variety of analysis tools, such as graph, ANOVA analysis, Pareto analysis, aggregation, fund charts, scatter schemas, partitioning, unstructured text analysis, and multivariate regression analysis. Best of all, there is no background in statistics or programming. As long as you have a basic understanding of spreadsheets, you will learn how to handle complex data sets so that you can get insights that are not possible using common business intelligence techniques.

Who should attend?

• Business professionals looking for data analysis tools to solve complex problems such as statistically valid web page optimization, and analyzing online customer feedback / online media.
• Analysts, researchers, marketing and sales professionals, administrators, supervisors, financial professionals, accountants, all professionals and staff responsible for performing administrative tasks and processes that include reporting, analysis and data processing .

How attendees will benefit?

Upon completion of the course, the participants will understand the following points:

• Obtain answers to complex data analysis questions without becoming statistical
• Learn which data analysis technique to use in different work problems
• Extract the most meaningful results from large and small data sets and multiple data types
• Learn basic text analysis tools and gain ideas from unstructured text data
• Use advanced parsing functions in Excel and open source tools
• Based on your basic understanding of spreadsheets to access powerful analytical techniques
• Improve your business efficiency and effectiveness

Programme Content:

• Hypothesis Testing and ANOVA
• Chi Square Test of Independence
• Pearson Correlation
• Exploring Statistical Interactions
• Data and Business Analytics; Working with data
• Controversy, disinfection and data formation (data scraping)
• Choose the correct variables, KPIs, CSFs (Data Analysis)
• Identify the Analysis Tools package from Excel
• Use of multivariate statistics, T test, factor analysis, linear regression, and other advanced techniques
• Review Additional Tools - JMP, Tableau, SPSS, R
• These were the most prominent vocabulary in the course of advanced tools and techniques for data analysis

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