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January 21, 2019

Big data trends that will get you fired (or hired!) in 2019

By 
Thomas LaMonte

Do stories in your newsfeed look like this:

“Every robot has its day—and that day happens to be your last day at work”

“I went to the robot invasion and all I got was this lousy USB drive … oh yeah, and I got fired”

“AI Advice: Ask for the human’s job”

Yep, it’s that time of year again: ‘Tis the season for automation doomsayers.

Relax—take a deep breath. Just look at me:

I’m not worried. So what if all our jobs are going to be taken over by robots? I’m not losing sleep over algorithms I couldn’t understand in a millennium of trying. I really can’t be bothered, but not because I’ve reached some tranquil nirvana in the face of out-of-control AI.

The truth is, there’s something else preoccupying the time I’d normally spend shaking in my sneakers about machines. It’s a much more unsettling, immediate boogeyman than is automation.

Humanity’s overlooked destroyer is … big data and analytics. Didn’t see that one coming, did you?

Well, it’s true: Big data is a likely reason you’ll be looking at the job classifieds. What company needs you when they have extraordinary data insights?

In the interest of keeping you employed, this article takes a look at four big data trends you need to keep an eye on in 2019.

Companies will start trusting data and stop trusting their gut

Eighty-five percent of companies are trying to be data-driven. What does it mean to be data-driven? It means making decisions from an authority of confirmable data insights rather than intuition or a personal hunch.

According to findings reported by the Business Application Research Center (BARC), 50 percent of all decisions in today’s business are based on information. When applied to business decisions, data insights bring consistency, legitimacy, and better outcomes when deciding how to win against your industry competitors.

The majority of businesses run on a singular vision authored by an individual or team of highly sharpened decision-makers. However, when business acumen is something that we can calculate and output with a computer, there’s a scramble for existing leaders and decision-makers to define the value they can offer.

When your organization stops giving the grumbles of your stomach an audience, what value do you now bring to the table?

The bar for data scientist skillsets is getting lower

Today, self-service analytics and business intelligence tools are all the rage. These easy to use tools enable anybody—regardless of technical background—to do the tasks traditionally owned by trained data scientists.

These data-savvy workers are called citizen data scientists or Citizen X, and according to Gartner, they’ll grow at five times the rate of traditional data scientists by 2020.

2020 looks to be a big year for Citizen X: More than 40 percent of data science tasks will be automated before 2020, resulting in increased productivity and broader usage by citizen data practitioners. And by the end of 2019, self-service BI users will produce more analysis than data scientists. (Gartner research is available to clients.)

Increasingly, data scientists will need to contend with sharing the analytics spotlight with Citizen X. Will data scientists take on the role of drill sergeant to data citizen recruits and drive analytics success, or slink away to other fields, industries, and functions as companies find Citizen X enough to meet their needs?

At the same time, Citizen X and the emerging data-fluent workforce—well versed in data science and how to apply insights to drive business goals—will drive you, a data illiterate, out of the office.

Your job interviews will be chaired by a panel of megabytes

If job interviews weren’t already nerve-wracking enough, now you need to deal with the silent judgment of data. Data analytics is increasingly being applied to the recruiting process. This means new hires should expect that on top of the typical hoops they jump through to land their dream job, in the background, their data profile will be running its own employment gauntlet.

Aggregated, analyzed, and comparing like candidates in a process beyond simple sorting, data will be a convincing source of quantitative reasoning to choose one candidate over the other. But big data also presents opportunities to refine the recruiting process.

Tom O’Neill, CTO and co-founder at Periscope Data, explains how big data has impacted his organization’s recruitment process:

“We know which sources work better than others. We know when the phone screen isn’t doing a good job, either rejecting too many or passing too many that don’t fit the criteria, and then we fix that. We review the data on a weekly basis. It’s a very iterative and very pragmatic process,” O’Neill says.

Ultimately, for O’Neill and Periscope Data, the priority is to use analytics to optimize recruiting and provide the best possible experience for the applicant:

“We want it to be an enjoyable interview experience for the candidates we meet with. And so I think we optimize for doing as much as necessary to evaluate the candidate, and then everything past that is to make sure that the candidate has a great experience.”

Think you’re safe? Big data will make white-collar jobs redundant too

You thought automation was the only thing to worry about—not quite. You may think you’re safe if you don’t have a job heavy on the manual tasks, but that’s not true either. There are professional business roles that will become obsolete in the era of big data and accessible analytics. Here are a few:

Human resources: We’ve already covered how big data will change recruiting from the perspective of the applicant. By extension, it will change the skill requirements needed for the HR specialist. HR professionals will be required to add the fundamentals of data analysis and data-driven decision-making to their expanding role.

Medical: Bernard Marr, contributing writer to Forbes, identifies that some aspects of a doctor’s job can now be done by machine learning and big data. For example, IBM’s Watson performed big data analytics of MRI data and was able to diagnose lung cancer at a higher rate of accuracy than humans can. How long until we’re all calling Dr. Big Data for our next doctor’s appointment?

Finance and insurance: When it comes to yearly tax returns in the United States, big data has already insinuated itself on both sides of the counter. The American public can easily rely on software that leverages big data to file their tax returns. On the flip side, the IRS uses machine learning to identify and investigate tax fraud. And get ready to say farewell to your insurance agent: Who needs a human to carry out the computations and formulas that determine their car insurance premiums when big data can do it in an instant?

Professional writing and journalism: Uh oh … guess this will be my last article. Looks like big data might be gunning for my byline too. Narrative science tools powered by machine learning and big data mean that a bunch of 1s and 0s will be able to write competent copy and hard-hitting news reports. Bernard Marr posits that stat-heavy topics such as finance or sports will be the first target, but I suspect it’s only matter of time before I’ll be out of a job too.

Recommendations: How can humans be more than their big data?

  • Master data skills before they become a prerequisite: Prepare to polish up your familiarity with a dashboard or analytics report, as data skills look to be a universal expectation in offices of the future (similar to basic computer skills or how to operate email today).
  • Find your new niche: Enhance your existing skillset and relevant experiences with data-driven uses cases: Initialize a data-driven approach to your department’s strategic priorities or develop policies to maintain data quality and compliance.
  • Further define humanity’s unique value: When all the potential job losses to big data transact, move to those remaining value-added jobs doable only with a human’s touch—or invent a new profession altogether.

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