Working in Analytics was Great until Big Data and ChatGPT hit the Scene
Santiago Tacoronte
Data & Productivity Futurist | Fueled +20% Share Price Increase at Mondelez | Changed 10 Million Lives at Philip Morris | Added $2M Yearly Incremental Revenue for Fly Dubai | Educator to 25K Future Analytic Leaders
Working in Analytics is moving from a desired and sexy job to a grind.??
The demand for Analytics products or data enablement to feed other applications has exploded in the last five years. Companies invest millions in Analytics and AI, and they want returns.
When I started on this 20 years ago, I was sure analytics would become fundamental for businesses. What caught me by surprise was the frenzy.
But what has the big data and AI hype changed in these 15 years?
1- Unrealistic Expectations
You might argue that this has always been on the table but with the democratization of data platforms, analytics, and AI, it seems like building intelligence is a matter of three clicks, and believe me, it is not.
Data is spread across locations, technologies, and functions. Particularly for established companies, it comes in different formats, from several systems and, in some cases, completely unstructured. Not to mention how many doors you sometimes need to knock on to get access.
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Yet many think that answering (extremely complex questions) is straightforward.?
Don't tell me you can't answer this, I have tried ChatGPT, and it has an answer to everything.
2- Everybody is an Expert
There has been a considerable increment in Data Literacy in the past few years. And while I defend that a data-driven organization is made of an analyst in all positions, it is also important to remark that only some are experts in topics like data architecture, visualization, data lakes, cloud computing, and programming.
3- ChatGPT only has some answers to your company's problems.
I am a massive fan of Generative AI like ChatGPT. However, it uses common knowledge and publicly available historical data, which means AI doesn't have a clue (yet) about what is going on inside your company.
On top of that, if you ever want GPT inside your business, you will still need to feed it with an enormous amount of data. And where is your data? (See point 1)
Disclaimer: I am still happily working in Analytics, but the game's rules have fundamentally changed. Analytics has become fully operational and critical to any business; therefore, there is less and less room for exploration and fun.?
General Manager - Europe, Executive @ Lingaro | Data & Analytics | HEC Paris
1 年Santiago, some true and resonating insights you bring up. Data Literacy is the key - but that cannot lead to disqualification of the actual workload required to build those intelligence engines - that are to bring these insights "in matter of three clicks". I wonder when will we start seeing a trend of "I made decision based on Chat-GPT insight and it was wrong".
Insurance Advisor at Allianz
1 年Great insight into how Big Data and ChatGPT are impacting analytics in today's world