Statistical Data Analysis

Step aside, coding: Time for analytical thinking in Big Data

The following is a contributed article by Stuart Wilson, VP EMEA at data analytics firm Alteryx


‘Big Data’ has continually been featured in tech and business headlines in recent years. But for every story filled on the promise of data, there are just as many on how few skilled workers there are who can understand and use it effectively. While there is growing support for STEM subjects, this hasn’t necessarily translated into addressing the critical data skills shortage that’s gripping the business community.

The importance of data in running an effective business – and in gaining faster, deeper market insight and competitive advantage – has been unequivocally recognised. Now the question is, where are the data workers who can make this happen? 

This is what many businesses are asking themselves, making data scientists in more demand than ever before. In fact, US-based online employment analysts at Glassdoor recently announced that data scientist is currently the best job in the US, based on pay, career advancement, and treatment in the workplace. The only problem is that there aren’t enough to go around…

But is that really the issue? And have businesses missed out on the real problem?


The battle begins: Coding vs. thinking analytically

There’s no disputing that the capability to set up, manage, and fix vast corporate databases is a job for an expert. Coders, programmers and systems architects with experience in data warehousing will always be crucial. However, many businesses are rushing to deal with the exponential growth of their data without considering what is truly needed. While the maintenance and broad management of data is a job for the technical experts, it’s no longer possible to leave data analysis to the few specialists.

Organisations have become obsessed with hiring people with very specific digital skills when it’s the common approach and thought processes that underpin each of these skills which are the most important. These technical disciplines rely on a methodical, analytical way of thinking and that’s what companies should look for in new hires and existing employees. This should happen across all departments, from HR through to finance and marketing. Every line of business needs analytical thinking.


Boosting business with self-service

The growth of self-service analytics tools has meant that coding is no longer a must-have skill for anyone who interacts with data. Legacy systems used to assume a level of technical proficiency of the user, but the latest generation of data solutions delivers a user-friendly interface.

With that potential hurdle addressed, the entire hiring dynamic shifts. These self-service tools enable businesses and recruiters to look at a far wider pool of candidates for any role, allowing them to consider factors outside of specific coding languages. Organisations can look at related experience, personality, and even raw intelligence, making it far more likely they’ll uncover the star hires that deliver business impact.

The shift away from reliance on specific people with specific technical capabilities also preserves the sense of agility that the modern business world demands. What happens if the business changes in the next 12 months, and a skill you’ve hired in is no longer relevant? Far better to hire recruits with an overarching methodical mentality than a group who can navigate a specific coding language. It’s far more important to have a logical mental workflow, know what data is most important to the business, and understand the particular business questions that need addressing. The ultimate knock-on effect of looking for people with this analytical mind set is that you’ll bring a richer, more diverse mix of people into the company, united by a systematic approach to business.


Looking to the future

Some of the top educational institutions, including Imperial College London and the London Business School, already offer modules, and even entire courses, in business analytics and related fields. This is driving change in the corporate world as the newest generation of MBA students and business leaders arrive with an analytical approach and an understanding of the value of analytics already in place.

The data-driven culture that many companies talk about no longer means that everyone should know SQL Server, Python or R. It means that every member of the business should understand that each of the firm’s decisions are made based on data, and that frequently interrogating data and making business decisions accordingly is how a company succeeds.


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