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The Future of Automation and Analytics

One of the most lucrative careers today remains that of the data scientist. Glassdoor ranked this job description as the best US job for both 2016 and 2017, indicating this position shows much promise for the future. But then again, with the rising importance and value of automating your operations, will this new phenomenon phase out the need for data scientists?

Considering the value and importance of data in today’s world of business, no one should be surprised to see the data scientist job description vying for top position as a desirable career. Now, the larger question looming is, “Can or will automation replace the role of the data scientist?” Or will data scientists find themselves ever more specializing, as many analytics become automated processes? Is there a world where automation and analytics become indivisible, or will there always be a demand for experts able to troubleshoot and expand the potential of analytics through smarter and more effective automation?

 

Understanding the Delicate Dance Between Automation and Analytics

You will find experts arguing both sides of this debate with equal vigor and impressive statistics and facts. On the one hand, analytics is the perfect type of process to undergo automation, as machines are known to gobble up data, regurgitate it in various forms for more refined digestion, and use formulas to determine appropriate actions to perform. On the other hand, by automating many of the analytical processes, this allows the data scientist to work at a higher level, instead of being consumed by the analytical process itself.

The idea that all the required intelligence is somehow included in any software automation package is unrealistic, to say the least. Just as a person might have a high enough IQ to classify them as a genius, until they consume and manipulate incoming data, they only contain the capacity for intelligent thinking and functioning. This is how intelligent automation software should be viewed: as having the capacity to perform at a higher and more reliable level than its human counterpart, but only after it has received the proper instructions to perform the task.

In other words, no matter how thorough or intricate your automation software may be, it still needs a human trained in the management and manipulation of data to visualize how best to work the data which has been collected.

 

The Relationship Between Data Scientists, Automation, and Analytics

The fact is, we still are not utilizing data to the maximum. We may believe we are standing at the very precipice of the cutting edge, but reality (and a dash of humility) informs us that each new point of progress reached becomes merely a new launching pad for improved and refined analysis. In other words, never expect automation software to do the thinking in place of a human; instead, expect quality automation programs that take instructions and parse them accurately and reliably.

An appropriate analogy of the relationship between data scientists, automation, and analytics could be that of a master chef (data scientist) with a sous-chef (automation and analytics). Of course, the sous-chef must have a working knowledge of recipes and the tools used to create culinary delights, but their real value and talent lie in clearing the decks and preparing the foods up to the point of the final finishes and the presentation to the customer.

The sous-chef performs important and essential duties, and at times can stand in for the master chef, but it is the master chef who has had the real-life experiences and creations which put them at the top of the kitchen hierarchy. Of course, the master chef can perform the many duties of the sous-chef, but this is not a good use of the valuable time of a master chef. Instead, the sous-chef should perform as many of the cooking and preparatory duties as possible, which creates a blank slate in which the master chef can focus on new creations and taste sensations.

In the same manner, the data scientist of the future will find more exciting and creative roles to play, while still maintaining strong and thorough oversight of the functionalities of analytics. A great data scientist can still perform outstanding analytics without depending upon automating the process, but a smart data scientist will always use the tools at hand to make their job easier and their results more certain.

Needless to say, the future of automation and analytics remains exciting and incredibly promising; for that very reason, the future of data scientists will also be stable and essential. As automation becomes more intelligent and intuitive, data experts will also find new ways of thinking, perceiving, and pursuing data analytics to improve and expand the ways we operate our businesses and experience our lives.

Through the proper marrying of automation and analytics, and with expert data scientists behind the steering wheel, the path ahead remains more than promising. It could be life-changing for our global society and businesses, offering us better, happier lives with a richer and more inclusive economy.

Murray Izenwasser

Murray consults with clients to create digital solutions that align with their vision, markets, customers and products. Prior to OZ, Murray co-founded Biztegra, a digital marketing, engagement and technology agency.

He also held senior positions at some of the world’s largest digital agencies, including Razorfish and Sapient, and began his career at what is now Accenture. An IASSC Certified Lean Six Sigma Yellow Belt™, Murray earned his B.S./B.A. in computer science and finance from the University of Florida.

Who is Murray Izenwasser

Murray consults with clients to create digital solutions that align with their vision, markets, customers and products. Prior to OZ, Murray co-founded Biztegra, a digital marketing, engagement and technology agency.

He also held senior positions at some of the world’s largest digital agencies, including Razorfish and Sapient, and began his career at what is now Accenture. An IASSC Certified Lean Six Sigma Yellow Belt™, Murray earned his B.S./B.A. in computer science and finance from the University of Florida.

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