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Analytical thinking is considered the top skill for success
According to the World Economic Forum - Future of Jobs Report, analytical thinking continues to grow in prominence, it is and will remain the #1 skill sought after by employers.
Why it matters:
“As they collect more data than ever before, companies are hungry for professionals who can make smart decisions based off of it.”
LinkedIn – The Skills Companies Need Most in 2019
Analytical thinking is hard
There are many books that describe the stumbling blocks and pitfalls that prevent us from being good at analytical reasoning. My favorite one is using intuition shortcuts, its beautifully explained by psychologist and Nobel prize in Economics Daniel Kahneman in his book Thinking fast and slow
Analytical thinking is the act of breaking down complex pieces of information into smaller and more understandable components. It involves dismantling data to decipher facts. It demands different areas of expertise, and as individuals we often possess only one of them. This colors what we pay attention to and how we tackle a question. In other words,
“If the only tool that you have in your toolkit is a hammer, everything looks like a nail.”
Our goal with SAP Analytics Cloud is to empower people to think and come up with the best and brightest insight. We want you to be data analyst rock stars. At SAP, we are convinced that Augmented Analytics is a game changer for developing analytical acumen.
I did an experiment on how Augmented Analytics would augment my own analytical brain. This isn’t about theory; it’s about rolling up my sleeves, building and augmenting my analytical skills. I recorded my experience these two videos, subtitles in English and Chinese are available.
Augmented Analytics in the Real World - Part 1
Augmented Analytics in the Real World - Part 2
About the College Scorecard data
I chose the United States College Scorecard dataset because I wanted to compare the use of traditional Data Discovery with Augmented Analytics. The College Scorecard dataset was perfect for that as it had been used twice in the Gartner BI Bake Off and a number of vendors took the challenge.
The dataset did require preparation steps, I used the new SAP Analytics Cloud data preparation for this, it made it possible to transform the dataset with its hundreds of fields.
The fun began when I started to use SAP Analytics Cloud augmented analytics capabilities, I felt like I had found a gold mine with the College Scorecard dataset.
Call To Action: expose rich & wide data models
In traditional BI, the best practice is to expose to BI users, data models that are limited to a specific domain so that domain experts can apprehend them. We need to revisit this.
The College Scorecard data is much wider than traditional BI data models. SAP Analytics Cloud handpicked the most relevant fields to help me answer my questions. With Augmented Analytics there is no need to limit data models as we usually do in Olap Cubes and Semantic Layers. It’s the opposite, the broader, the richer the data is, the best insight we can get on complex questions.
Other Augmented Analytics Use Cases
My experiment focuses on analytical thinking on complex questions.Augmented Analytics also has major impacts on how more casual BI users will get answers to their questions. Folks whose pay check does not depend on answering difficult questions. For more info, check-out the blogs from my colleagues:
Priti Mulchandan on Smart Insights
Sofiya Muzychk on natural language search
Learning on augmented analytics capabilities in SAP Analytics Cloud
