Fundamentals of Big Data Analytics & Data Storytelling

The Rocks Stars of Data: Fundamentals of Big Data Analytics & Data Storytelling (Two Days)

To find out more about our next scheduled public learning session on June 27-28, 2017 in Ortigas or to set-up an in-house training, send an e-mail to analytics@dmaiph.com

Learning Session Description

Just about every company is looking for ways to get more value out of the data in our businesses. Actually finding the most important insights in our business data and communicating them in a compelling way is what separates data-driven companies from the rest of the pack.

Having access to well managed Big Data will make our businesses more successful. Using well told data stories as change drivers within the modern organization. In the end, a blend between art and science will give data-driven companies the edge they need to prosper.

This two day course takes students from the fundamentals (what should we be measuring and why?), how we need to manage our data (where to store it), through to the elements of good visualization design (what does a good chart look like?) and finally to proficiency in data storytelling. By the end of the course, students will know how to master the use of their Big Data to produce engaging, cohesive and memorable data stories using Excel and PowerPoint.

Learning Session Objectives

  • Apply Cutting Edge Technologies to Organize, Interpret, and Summarize Big Data in Your Business
  • Create a Process to Analyze Data and Identify Patterns Not Apparent at First Glance
  • Reduce “Analysis Paralysis” and Go from Hard Data to Well-Reasoned Conclusions in Less Time
  • Develop a Deeper Understanding Of How Best To Deploy Analytics Techniques

In this session, your organization will be able to use:

  • Specific skills to effectively frame the problem you’re addressing to uncover key opportunities and drive growth
  • How to simply and quickly amplify decision making by separating the signal from the noise
  • A framework for asking the right questions, allowing the ability to link analytics to business strategy
  • Visualization best practices for the most common charts used in business
  • Guidelines on best practices for linking visuals together into a cohesive story that concludes with actionable recommendations
  • Applied examples regarding trend analysis, sampling, confounding variables and the statistical aspects behind data storytelling

In this session, your participants will be able to:

  • Bring out patterns in data that were not apparent at first glance
  • Shorten the time between analysis and action to avoid “analysis paralysis”
  • Create complete data stories and know how to present these stories in an engaging way to upper management
  • Generate statistically robust data driven insights that inform decision making in the business setting
  • Build stakeholder support for project initiatives using data
  • Know how to select appropriate chart types for a given dataset (e.g. When to use a bar chart versus a pie chart, a line graph versus a bubble chart)
  • Know how to design aesthetically pleasing data visualizations that adhere to the principals of good design

Who Should Attend

  • Business Analysts, Data Analysts and other Analytics Professionals
  • Managers of analysts or staff who spend a significant amount of their time collecting, analyzing and reporting data.
  • Graduate hires who are on track toward a career in analytics or data science
  • Executives and managers who want to create more engaging and impressive presentations with Excel and PowerPoint
  • Professionals already working in analyst positions, including (but not limited to) positions involved with data preparation, data analytics, digital and marketing analytics, customer and market analysis
  • Any other business professional who would like to get more out of their Big Data and to tell better stories with data

Laptop Required Specs

  • Intel i3 processor, 2GB RAM. Either Mac or Windows operating system

Software Requirements

  • Excel 2010, 2013 or 2016 and PowerPoint 2010, 2013 or 2016

Section One – Big Data—It’s Not Just Size That Matters

  • Discuss the Fundamentals of Big Data Analytics,
  • Identify Who In Your Organization Uses Big Data,
  • Come Up with A Data Map to Analyze the Big Data in Your Business,
  • Establish Clear Objectives When Analyzing Big Data,
  • Define What Is an Analytics Centric Culture.

Section Two – Big Data – How to Collect It and Where to Store It

  • Recognize and Apply Various Data Collection Methods,
  • Identify and Resolve Problems Associated with Data Collection,
  • Consider the Various Types of Data Storage,
  • Examine the Difference Between Data Warehouses and Data Lakes,
  • Determine When to Use Data Blending in Your Analysis.

Section Three – Interpreting Your Data and Analysis 



  • Recognize When to Employ Descriptive, Predictive or Prescriptive Analytics,
  • Learn how to build a Data Model Prototype
  • Articulate the Importance of Accurately Interpreting Data,
  • Mitigate and Analyze Risk, Uncertainty, And Probability,
  • Spot Patterns and Trends Through Statistical Analysis.

Section Four –  Using Business Intelligence Tools with Big Data

  • Discover How to Find the Most Important KPIs,
  • Learn How to Build Better Management Reports,
  • Optimize Your Use of MS Excel For Big Data Analytics,
  • Undergo an Overview of BI Tools,
  • Introduce the Concept of Data Visualization.

Section Five – Overview of the Four Keys to Data Storytelling

  • Knowing your audience
  • Preparing your data
  • Choosing the right visual and designing it well
  • Telling the story
  • Tables Vs. Charts Vs. Single Metrics – What to Use and When?

Section Six – The Visualisation Arsenal

  • The Histogram – The most underutilized visualization in business
  • The Bar Chart – The king of flexibility, guidelines on vertical and horizontal variations
  • The Stacked Bar Chart – The case for and against stacked bar charts
  • The Pie Chart – Theory and controversy, show down versus the bar chart
  • The Scatter Plot – Theory and guidelines for large datasets
  • The Line Chart – Theory, comparison with clustered bar charts, discussion on dual axis line charts, the slope chart (a special case of the line chart)

Section Seven – The Elements of Data Visualisation Design

  • Above all else, show the data
  • Tufte’s war on chart-junk and Tufte’s data-ink ratio
  • Using color to focus attention
  • Dimension, perspective and 3D
  • The Gestalt principles of visual perception (Proximity, Similarity and Enclosure)

Section Eight – Adding the Narrative to Your Data Story

  • Designing your visuals and narrative around ‘The Big Takeaway’
  • Planning your story flow – untangling a ‘spaghetti’ line chart
  • Delivering insights
  • Positioning and designing insights
  • Impact titles
  • Creating memorable soundbites
  • From reporting to strategy – Is your data story actionable?

Laptop Required Specs

Intel i3 processor, 2GB RAM. Either Mac or Windows operating system

Software Requirements

Excel 2010, 2013 or 2016 and PowerPoint 2010, 2013 or 2016

Case Studies and Exercises

Case studies and group exercises will be used throughout the two-day class. In these activities, the group is divided into teams. Each team will analyze datasets and tell data stories using the principals learned in the various learning sessions. These exercises will also use elements from the case studies as we progress from finding data, to conducting analysis on the data and finally presenting the data.

Learning Investment for 2-day Seminar: 

Exclusive Offer!!
Early Bird
P 12,000.00 + VAT
(Pay the full amount on or before May 26, 2017)

Group Rate (Minimum of 5)
P13,000.00 + VAT

Regular Rate:
P 14,600.00 + Vat
(starting May 27, 2017)

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Analytics and Data Science Training – DMAIPH offers a wide range of analytics centric training solutions for professionals and students via public, in-house, on-site, and academic settings. We tailor each training event to meet the unique needs of the audience. If you need empowerment and skills enhancement to optimize the use of analytics in your organization, we are here to help. Contact DMAIPH now at analytics@dmaiph.com or connect with me directly to set up a free consultation to learn which of our DMAIPH analytics training solutions is best for you.