Foundation of Data Analytics

Categories : Data Analytics Course Online

This Course Includes:

Enhance your data analytics skills with a Data Analytics Foundation course and lab. The course and lab offer interactive learning resources that help candidates learn how to use data typologies, data analytics tools, business statistics, data visualisation with the working and value of data. The course also covers the subject areas like processing, collecting, storing, and analysing to help you in advancing your professional career. The course will help you in advancing your professional career.

Lessons 1: The Value of Data

  • Opening Case
  • Introduction
  • Managers and Decision Making
  • The Business Analytics Process
  • Business Analytics Tools
  • Business Analytics Models: Descriptive Analytics, Predictive Analytics, and Prescriptive Analytics
  • Summary
  • Discussion Questions

Lessons 2: Working with Data

  • Sample Data
  • Moving Quickly with the Control Button
  • Copying Formulas and Data Quickly
  • Formatting Cells
  • Paste Special Values
  • Inserting Charts
  • Locating the Find and Replace Menus
  • Formulas for Locating and Pulling Values
  • Using VLOOKUP to Merge Data
  • Filtering and Sorting
  • Using PivotTables
  • Using Array Formulas
  • Solving Stuff with Solver

Lessons 3: Data Typologies and Governance

  • Introduction
  • Managing Data
  • The Database Approach
  • Big Data
  • Data Warehouses and Data Marts
  • Knowledge Management
  • Summary
  • Discussion Questions
  • Problem-Solving Activities

Lessons 4: Business Statistics

  • Introduction to Probability
  • Structure of Probability
  • Marginal, Union, Joint, and Conditional Probabilities
  • Addition Laws
  • Multiplication Laws
  • Conditional Probability
  • Revision of Probabilities: Bayes' Rule
  • Introduction to Hypothesis Testing
  • Testing Hypotheses About a Population Mean Using the z Statistic (σ Known)
  • Testing Hypotheses About a Population Mean Using the t Statistic (σ Unknown)
  • Testing Hypotheses About a Proportion
  • Testing Hypotheses About a Variance
  • Solving for Type II Errors
  • Formulas
  • Supplementary Problems
  • Analysing the Databases

Lessons 5: Optimisation and Forecasting

  • Why Should Data Scientists Know Optimisation?
  • Starting with a Simple Trade-Off
  • Fresh from the Grove to Your Glass…with a Pit Stop through a Blending Model
  • Modelling Risk
  • Wait, What? You're Pregnant?
  • Don't Kid Yourself
  • Predicting Pregnant Customers at RetailMart Using Linear Regression
  • Predicting Pregnant Customers at RetailMart Using Logistic Regression
  • For More Information
  • Correlation
  • Introduction to Simple Regression Analysis
  • Determining the Equation of the Regression Line
  • Residual Analysis
  • Standard Error of the Estimate
  • Coefficient of Determination
  • Hypothesis Tests for the Slope of the Regression Model and Testing the Overall Model
  • Estimation
  • Using Regression to Develop a Forecasting Trend Line
  • Interpreting the Output
  • Summary
  • Formulas
  • Supplementary Problems
  • Analysing the Databases

Lessons 6: Other Data Analytic Tools

  • Getting Up and Running with R
  • Doing Some Actual Data Science

Lessons 7: Data Visualisation

  • Why Do We Visualise Data?
  • How Do We Visualise Data?
  • Colour
  • Common Chart Types
  • When Our Visual Processing System Betrays Us
  • Every Decision Is a Compromise

Hands-on LAB Activities

The Value of Data

  • Summarising the Aspects of Business Analytics and its Applications

Working with Data

  • Freezing the Top Row
  • Using the AVERAGE Function
  • Using Relative, Absolute, and Mixed References
  • Formatting Numbers
  • Applying Conditional Formatting
  • Using the Paste Special Feature
  • Analysing Data Using a Line Chart
  • Creating a PivotTable Automatically
  • Calculating the Minimum and Maximum Sales Value
  • Using the SUM Function
  • Using the MATCH Function
  • Using the VLOOKUP Function
  • Sorting Data

Data Typologies and Governance

  • Understanding Big Data
  • Understanding the Relational Database Model

Business Statistics

  • Understanding Business Statistics
  • Calculating the Statistics

Optimisation and Forecasting

  • Using the SUMIF Function
  • Using the IF Function

Other Data Analytic Tools

  • Using the factor() Function
  • Using the str() Function
  • Using the sqrt() Function
  • Using the matrix() Function
  • Using the length() Function
  • Using the rbind() and cbind() Functions
  • Using the aggregate() Function
  • Using the order() Function
  • Using the predict() Function
  • Using the print() Function
  • Using the summary() Function
  • Using the which() Function

Data Visualisation

  • Visualising Data
  • Understanding Data Visualisation
  • Creating and Analysing Chart Types

Exam FAQs

FAQ's are not Available for this course.

Summary

Standard:

Foundation of Data Analytics

Lessons:

7+ Lessons

Delivery Method:

Online

Language:

English

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