Data Mining and
Big Data Analytics Using SPSS

The Data Mining and Big Data Analytics have become a household name and have provided companies with indispensable tools for data driven decision making, have increased productivity and generated highly effective innovations. They have also created some controversies, however not due to the flaws in Data Mining and Big Data Analytics, but due to the flaws in the people who were using or abusing them. This Anderson training course is designed to provide the insight into the positive aspects of the Data Mining and Big Data Analytics, to help the people avoid the pitfalls and also to understand how to acquire highest benefits. In order to do this, the training course actually shows the delegates the ways to harness the benefits, without the need to become IT and computer programming guru. There are many software packages for Big Data mining and Big Data Analytics, however many of these tools are mainly programming languages, and although free, they require a knowledge of computer programming. As the data rises, the number of people who can perform the Data Mining and Big Data analytics should also rise, to handle the tide, and by using one of easiest to handle, big data analytics software is SPSS.

This software helps the people who want to use the power of Data Mining and Big Data analytics, but are not inclined to learn programming, and it is well suited and highly developed for everyone who wants to get the power of Big Data through the graphic interface, instead of coding.

By attending this Anderson training course, delegates will be able to:

• Understand the power of Big Data and Big Data Analytics
• Harness the benefits of graphical interface of SPSS for Big Data Analytics
• Learn the concepts of data analysis and visualization
• Apply the drag and drop functionality for data visualization
• Acquire the knowledge of advanced analysis of big data, like sentiment analysis in SPSS
• Get aquatinted with the theory of data analytics and the methods used in machine learning
• Learn advanced concepts of data analytics like clustering, association and sentiment analysis

This Anderson training course is suitable to a wide range of professionals but will greatly benefit:

• CTOs, CIOs and Engineers
• Data Scientists, Data Analysts
• Statisticians and technology personnel
• Marketing and research specialists
• Consultants
• HSE managers
• Anyone related or interested in Data Analysis who needs the drag and drop interface

• Getting to know SPSS
• Starting SPSS and Working with data files
• Descriptive Statistics
• Frequencies (categorical variables)
• Central tendency, standard deviations, and range (continuous variables)
• Getting help and running tutorials

• Using graphs to describe and explore the data
  • Histograms
  • Bar graphs
  • Boxplots
  • Line graphs
• Calculating total scale scores
• Transforming variables
  • Recode procedure
  • Compute procedure
  • Select cases procedure
  • Split file procedure
• Reliability analysis using coefficient alpha (also known as Cronbach’s alpha)

• T-test, one sample t-test, independent and dependent sample t-test
• Analysis of variance (ANOVA)
• Correlation and Pearson r correlation coefficient
• Linear regression-simple and multiple linear regression
• The chi-square goodness of fit and test of independence procedures
• Autocorrelation and time series analysis

• SPSS Modeler and its main elements
• Clustering analysis, using k-means
• Association rules and apriori algorithm
• Logistics regression
• Forecasting using the Autoregressive Integrated Moving Average (ARIMA) model
• Building a decision tree model
• Sensitivity analysis of texts in SPSS

• Big Data Analytics programs
• Brief introduction to R
• SPSS Modeler-R integration
• Introduction to Python
• SPSS Modeler Python Integration
• Putting it all together

Anderson Certificate of Completion will be provided to delegates who attend and complete the course