Data Visualisation & Analytics using Excel

An Interactive 10-Day Training Course

Data Visualisation & Analytics using Excel

NASBA

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Modules

This training course is split into the following modules:

Module I - Data Visualization

Module II - Data Analysis Techniques

Course Outline

Module I: Data Visualization

Day 1

Telling a Story through Data Visualization

  • The Necessity of Data Visualization
  • Basis of Visual Grammar
  • Creating a Context
  • Determining the Users
  • Filtering the Data
  • Common Visualization Software
Day 2

Balance between Statistics, Design and Aesthetics

  • Bar Charts, Line Charts and Pie Charts
  • Advanced Charts (bubble charts, waterfall charts, etc.)
  • Combining the Data from Excel with PowerPoint Presentations
  • Let the Data Speak for Itself
  • Choosing the Volume of the Data
  • Color Management
  • Complement of Words and Pictures
Day 3

Common Data Visualization Methods

  • Maps and Charts
  • Dashboards
  • Infographics
  • Sankey Diagrams
  • Spider Charts
  • Geographic Referencing
  • Multimedia Presentations
Day 4

Creating the Presentation

  • Preparing the Data for the Presentation
  • Choosing the Story
  • Visual Cues
  • Interactive Presentations
  • Order Logic
  • Adopting the Appropriate Display
  • Avoiding Data Chaos
  • Voice of the Customer
  • Data Visualization Examples
Day 5

Promoting and Updating the Data Visualization

  • The Narrative Structure
  • Piñata Principle
  • Steal the Attention of the Audience
  • When and How to Update the Data Visualization
  • Use of Data Visualizations in Different Industries
  • Applying the Data Visualization at Your Workplace

Module II: Data Analysis Techniques

Day 6

Logical and Reliable Data Analysis, Descriptive Statistics, and Pivot Tables

  • Importing data into Excel
  • Best practice when analyzing data
  • Analyzing and representing coded data
  • Descriptive statistics and their real meanings
  • Performing a frequency analysis
  • The use of pivot tables and pivot charts
  • Noisy and incomplete data, statistical significance and dealing with outliers
Day 7

Data Mode Shape Analysis

  • Plotting data against time
  • Generating data mode shapes
  • Fitting curves to data
  • Correlating mode shape to time-based events
  • Interpreting time series analyses
  • Moving average calculations
Day 8

Scenario Analysis and Interactive Spreadsheets

  • Representing analytical problems as multi-input, single-output (MISO) systems
  • Deterministic systems analysis
  • What if and visual scenario analysis
  • Dynamic / interactive spreadsheets and the use of forms control
  • Moving window, conditional and adaptive calculations
  • Measuring the sensitivity of calculated variables
Day 9

Regression Analysis and Correlation

  • Equations of curves
  • The prediction of future behavior using data shape – regression analysis
  • Linear, polynomial, exponential and power curve fits
  • The dangers of over-fitting
  • Data end effects
  • Goodness of fit (sum of square error – SSE) and R2
  • Evaluating equations, solving equations, and using Solver
  • Correlation and causality
Day 10

Data Driven Methods and Analysis of Variance

  • Non-deterministic system
  • Data driven methods
  • One step ahead future prediction using data science (multivariate correlation)
  • Single factor analysis of variance (ANOVA)
  • Two factor analysis of variance
  • A demonstration of artificial intelligence – the travelling salesman problem
Certificates
  • On successful completion of this training course, GLOMACS Certificate will be awarded to the delegates.
  • Continuing Professional Education credits (CPE): In accordance with the standards of the National Registry of CPE Sponsors, one CPE credit is granted per 50 minutes of attendance.
Providers

Endorsed Education Provider

NASBA
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