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Posts Tagged ‘Data scientists’

Those in the I.T. and ERP arena who implement software and hardware solutions for a living have long known – or at least, should know – that speaking the language of business is as important as speaking the various languages of technology.  A recent article on the shortage of data scientists in the U.S. in the 21st century makes that point clear, noting that a McKinsey analysis recently predicted a shortage of 250,000 data scientists here by 2024.  Worth noting: Countries like Malaysia are busy building national programs as they seek to fill the gap by becoming a global hub of data science talent.

An article from information-management.com reinforces the point, noting that data is becoming more ubiquitous in every organization and data scientists are bound to grow in importance.  “Today’s students will be the first data-native employees of the future, and it’s critical that they understand data science, how data science is changing and how data science solves real world problems,” says Ashish Thusoo, CEO and chief data scientist at Qubole a “data-as-a-service” company in Santa Clara, California.

As the impact of AI (artificial intelligence), machine learning and big data all seep into the business world, it becomes more important than ever that tomorrow’s data scientists can optimize business processes, think in the language of business and apply human creativity to solving real-world business problems.  A lot of the tedious and manual data entry work is going to be performed by machines and algorithms, and the pace of change will only accelerate.  The critical question then becomes: Can we teach our students and employees to master the arcana of data while thinking like business people?

Mr. Thusoo puts it nicely in an article found here: “Data scientists will need to be able to think like MBAs and MBAs will need to think like data scientists. That requires an interdisciplinary approach to education.”

 

These future data masons will be working across multiple disciplines and communication skills will be of great importance.  They will need to be collaborators, understanding the various aspects of the business while being effective communicators.  They’ll require multi-disciplinary talents for sure, and be able to speak a bit of many ‘languages,’ like marketing, production, sales, accounting and leadership.

And of course, the learning never stops.  These workers will require social skills, data skills and overall learning skills to go with foundational hard technical skills.

In the end we are learning that data science is rapidly evolving into a profession that requires a whole suite of both soft and hard skills, and that we will need a whole lot more folks to fill these roles.  But then again, today’s best business analysts, software engineers and enterprise implementation teams have always known this.

The difference going forward is that we are going to need a whole more of us.

 

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