The 4 Levels of Analytics and Data Literacy

George Firican
3 min readSep 26, 2022

We are living in a data-driven world where data is produced everywhere. It is a currency that is not going away. However, Data is just data if it just sits there. Nothing happens unless action is taken, and that’s Analytics.

In today’s episode, we speak to Jordan Morrow, the godfather of Data literacy, advisory board member at Diana AI, and the head of data, design, and analytics at Brainstorm Inc. Jordan has helped many companies and organizations across the world, including the UN, to build an understanding on data literacy.

In this session, we dive deep into Jordan’s journey into data literacy, creating the first world program for it, and the four levels of analytics. That is, descriptive, diagnostic, predictive, and prescriptive. Besides, he expounds on the interconnection between data literacy, culture, and fluency and how data culture hinders the success of data analytics.

If you’re looking to build your data storytelling, Jordan gives tips from getting your context right to communicating your analysis well.

Listen to the LightsOnData Show podcast episode on the 4 levels of analytics

You will want to hear this episode if you are interested in:

  • [00:27] Jordan Morrow’s Journey
  • [03:36] The 3C’s of Data Literacy
  • [04:19] The four levels of Analytics
  • [10:15] How Jordan got into the data literacy field and created a program for it
  • [16:02] The different levels of data literacy
  • [18:35] The interconnection between data literacy, data fluency, and data culture
  • [23:06] The 5C’s of data storytelling
  • [24:31] Instances where the end result of a project is delivered but no action is taken
  • [27:51] Who owns data literacy in an organization
  • [31:11] How businesses are adapting cognitive analytics
  • [35:34] The silo between data analytics strategies and business strategies
  • [39:40] Morrow’s book on Data Literacy
  • [41:49] Having data literacy in the academic curriculum

Notable Quotes

  • 95% of your data and analytical work will be descriptive and diagnostic, while the rest will be predictive and prescriptive.
  • When we understand why something happens, there is your insight. That’s how you make business decisions.
  • Data is a currency that is not going away.
  • The number one roadblock for data and analytics success is data culture. It has nothing to do with technical skills or the quality of data.
  • The data and analytical strategy need to tie back to the business strategy.
  • We have two wolves inside of us. One is positive with all positive thoughts, and the other is the opposite. It depends on the one you feed. That’s the one that is going to grow.
  • The companies that do not get on board in the next couple of years could be the ones that fall by the wayside in the next five to ten years.
  • Data literacy is not a trend but a necessity. It is here to stay.

About Jordon Morrow

Jordan Morrow is known as the “Godfather of Data Literacy”, having helped pioneer the field by building one of the world’s first data literacy programs and driving thought leadership. Jordan is Head of Data, Design, and Management Skills at Pluralsight and a global trailblazer in the world of data literacy, having built one of the world’s first data literacy programs. He served as the Chair of the Advisory Board for The Data Literacy Project, has spoken at numerous conferences around the world, and is an active voice in the data and analytics community. He has also helped companies and organizations around the world, including the United Nations, build and understand data literacy.

When not found within his work of Data, Jordan is happily married with 5 kids. Jordan is also an avid trail runner and loves fitness, entering and racing in multiple ultra-marathons, and having fun adventures in the mountains. Jordan is an avid reader, often reading (or using Audible) to go through multiple books at a time.

Resources mentioned

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George Firican

Data governance & BI professional, ranked among Top 5 Global Thought Leaders on Big Data, founder of and Co-Host of the Lights On Data Show.