2020 had been a year where Technology and CIO have been in Spotlight, where they have tried to move their company through this pandemic and somewhat establish their company in new normal.
As we are heading now and starting with 2021 the CIO have been talking specifically about AI. A Need to have a checklist of sorts, keeping in mind the decisions they have been making, whether be it hiring new talents and new projects to consider.
Let’s start with the role of the CIO in picking the talent that is needed to pull off AI projects in companies.
Since 2020 was special due to disruptions in businesses. The AI has been becoming more important to projects that may be talked about before and are being accelerated now.
The speed of movement is rapid within new paradigms, for example, commerce, supply chains, e-commerce, shipments, etc.
This requires being more mindful of data and be reactive to how things changing constantly and much faster.
If we talk about AI in a very global sense because it can process data very fast, getting insights very fast, the data we are talking about here is volumes of data.
So now, what you need to have in your company to achieve the goals of these companies?
One practice these companies have been doing for years is growing data lakes. Data Lakes have been popular among large scales companies that have grown tremendously in the past few years.
But to maintain these Data Lakes, the juniors should know how to pull these data quickly out of their Data Lakes and serve them to the data science teams that can transform them within hours into meaningful insight.
So, Data Engineers are going to be required much more in the next few years.
Because without those data miners who will feed those AI Algorithms, these projects mean nothing. Because the AI we have today doesn’t work without these data.
Data Science has been growing for the last few years. So, data scientists are going to be needed for these companies to achieve their goals. Data scientists are developing the and AI required for these projects. Where Data scientists are being hired to perform analysis work on data.
But, now with more technological developments, only data scientists are not enough, but we need engineers that develop those machine learning-based automated products. Be it a project or an internal product.
Who, continuously work for the company that is going to be need of such products.
So, Data Engineers along with Data Scientists are going to be looked out by CIOs.
Here, the talent gap that needs to be addressed is at the middle level who can train the juniors and have considerable experience in this field.
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