Take your Analytics Skills to the next level working in an environment (software) you are already familiar with: Excel. Discover PowerPivot and Power Query and transform your data to build fully interactive dashboards and reports. Gain an introductory knowledge of Open-Source software such as R and Python to complement Excel in data wrangling and data visualisation. You will learn new ways to import data from various sources and data preparation in SMART ways instead of losing 80% of your time in data cleaning instead of data analytics.


The course will also cover the four axes of Data Analytics:

  • Descriptive Analytics (to answer questions on WHAT HAPPENED based on historical data)
  • Diagnostic Analytics (to answer questions on WHY things happened)
  • Predictive Analytics (to answer questions on WHAT WILL HAPPEN based on historical data)
  • Prescriptive Analytics (to answer question about WHAT SHOULD be done)

The workshop will help you to fully understand the data analytics landscape and prepare yourself with the best tools to deliver



Course Structure: 

• The Data Analytics Landscape
• Excel Power Pivot and Excel Power Query
• Creating “What-If” scenarios 
• Statistical analysis with Excel
• Data Visualisations with Excel Dashboards and Reports
• Analyzing large amounts of data and reporting in a meaningful way 
• Get better visibility into data from different perspectives
• Slicing data into various views on the fly
• Introduction to the DAX language
• Introduction to R
• Data Visualisation with “ggplot2”
• Introduction to Data Science
• Introduction to Power BI

Day One: Advanced Data Analytics

Module 1: The Data Analytics Landscape

  • Why Data Analytics?
  • Qualities of a Good Data Analyst
  • Tools for the Job


Module 2: Analytics with Excel

  •  Pivot Tables Fundamentals
  •  Anatomy of a Pivot Table
  • Formatting Your Data for Pivot Tables
  • Customizing a Pivot Table
  • Grouping, sorting and Filtering Pivot Data
  • Performing Calculations in Pivot Tables
  • Using Pivot charts and Other Visualisations
  • Working with Slicers


Module 3: Advanced Analytics with Excel

  • Introduction to PowerPivot in Excel
  • Data Modeling with PowerPivot
  • Best Practices in Data Modeling
  •  Relationships in Your Data Model
  • Getting Data From Different Sources


Module 4: Power Query (Data Transformation)

  • What is Power Query?
  • The Power Query Editor
  •  Reshaping Your Data
  •  The M language


Module 5: Advanced Charts with Excel

  •  Introduction
  •  The Waterfall Chart
  •  The Bullet Chart
  • The Thermometer Chart
  • Other Data Visualisations Tools


Day Two: Advanced Analytics

Module 1: The DAX Language

  • DAX Operators
  •  Comparison Operators
  •  Arithmetic Operators
  • Aggregate Functions
  •  DAX functions for Time Analytics


Module 2: Measures and Calculated Columns

  • Introduction to the DAX Language
  •  Calculated Columns
  •  Measures
  •  Measures and Context
  •  Time Intelligence
  • The FILTER () Function
  •  Using RETURN in a Measure


Module 3: DAX Language: Some important FUNCTIONS

  • Table Functions and CALCULATE
  • FILTER and ALL Functions
  • ALLSELECTED Function


Module 4: Introduction to Data Science

  • What is Data Science?
  • Tools used by the Data Scientist
  •  Should You Take Your Analytics into Data Science?


Module 5: Open-Source Software

  • Introduction to R
  • Why R?
  •  Data Visualisations in R (the ggplot2 package)
  •  Practical Examples
  •  Other Open-Source Software for Advanced Data Analysts


Module 6: Way Forward

  •  Introduction to Power BI
  •  Where do I go from here?
  • Keeping Track of Your Data Analyst Goals
  • Other Resources to improve Your Data analyst Skills

100% Money Back Guarantee

We're so confident of the quality of our courses that we back them up with a 30-day, 100% money-back guarantee. If for any reason you are not satisfied with this course, contact us within 30 days of purchase and you will be given a full refund subject to the our terms and conditions. Go ahead! You have nothing to lose


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