The popularity of social media, digital communication, web-based services, the Internet of Things and even digital images has rapidly increased the volume of data we generate each year. And industries across the board rely on that information. It’s no wonder that demand for data science and data analytics professionals is off the charts.

A recent Workforce Report from LinkedIn revealed that shortages in these areas exist in almost every large U.S. city. In fact, the national shortage of professionals with data science and analytics skills is more than 150,000 people.

If you’re looking for ways to increase your impact in the workforce and become a more marketable candidate in your industry, fine-tuning your data analytics skills could transform you into the coveted employee companies are desperate for. Before learning about some of the sought-after skills you could add to your resume, it’s a good idea to look into what the future holds for data analytics professionals.

Data analytics jobs have a bright future

In their process of retrieving data and analyzing it, data analytics professionals draw meaningful conclusions that can greatly impact business initiatives. The World Economic Forum’s The Future of Jobs Report 2018 identifies that data analysts are needed across industries, from healthcare to financial services. The importance of the role is also prominent across geographic locations. Demand is growing in North America, Asia and Europe alike.

The demand for data analytics professionals is growing faster than ever, with all information indicating that will remain the case for years to come. Industries of every type recognize that being able to analyze big data presents opportunities for sales, marketing, human resources and other important business areas.

10 Data analytics skills in high demand

As companies increasingly rely on big data in their most critical decisions, it’s clear that data science and data analytics skills are becoming more important. We dug into the research on the topic and used real-time job analysis software to examine more than 160,000 job openings from the last year to learn more about the skills employers seek most.*

Technology skills

Many of the primary skills employers expect from data analysts are related to specific programming languages, libraries and tech tools. The following five are particularly essential.

1. SQL

Short for Structured Query Language, SQL is among the most sought-after skills in the data analyst and business intelligence job postings from the last year. This domain-specific programming language makes retrieving data possible, and it provides analysts with a way to access and manipulate large amounts of information in a relational database.

2. Python

Python is another in-demand programming language. This object-oriented, high-level programming language tends to be user-friendly for beginners. It paves the way for sophisticated data analysis — a majority of the libraries used for data science and machine learning have Python interfaces. It can also be a powerful tool for data visualization.

3. Tableau

A common analytics platform and data visualization tool, Tableau allows analysts to transform information into insights that drive action. This software empowers users to prepare data for analysis and visually present data for easy interpretation, even for non-technical users.

4. R

Known in simple terms as a programming language, R is really an integrated suite of software facilities for data manipulation, calculation and graphical display. It helps simplify big data analysis and performs a wide variety of statistical and graphical techniques. R can also enable predictive analysis on real-time data.

5. Hadoop

The Apache Hadoop software library is an open-source platform that processes large data sets across computer clusters using simple programming models. The primary benefits of this software framework are found in its ability to provide massive storage for all kinds of data, its vast processing power and its ability to handle an immense number of tasks concurrently.

General skills

In addition to the skills above, there are a number of more general competencies that will help you succeed in the data analytics realm. The following skills came up repeatedly in our research.

6. Machine learning

A branch of artificial intelligence, machine learning involves teaching computer systems that are empowered by data and algorithms to make predictions without being programmed to do so. It’s a subfield that combines data science, math and software engineering. Data analysts with an in-depth understanding of machine learning can leverage its capabilities for applications in marketing, customer service, social media and product development.

If you’re curious to learn more on the topic, check out University of Massachusetts Global’s webinar, “Intro to Machine Learning.”

7. Statistics

The process of analyzing massive amounts of data can be complicated and multifaceted. Analyzing unstructured data is often impossible to do qualitatively, so it must be done quantitatively. At a minimum, data analysts should have a sold grasp of basic statistics. But an in-depth understanding of statistical concepts like linear regression, classification and resampling methods can go a long way.

8. Business intelligence

Advanced statistical and technical skills are useful in data analytics, but a strong business acumen is also essential for making an impact on an organization. Understanding the basic challenges facing your company can help inform insights, predictions and recommendations. Business intelligence, specifically, refers to using insights gathered from data to inform business decisions, improve the organization and increase profitability.

9. Communication

Data analytics professionals are not only tasked with sifting through and understanding massive amounts of data — they also need to effectively communicate their findings to stakeholders. A core part of the job requires proficiency in storytelling. As data becomes increasingly essential to decision-making across industries, analysts should be able to translate complex technical information into something simple enough for their audience to understand.

10. Critical thinking and problem solving

Data analytics, as a practice, hinges on the ability to objectively examine information that’s relevant to a problem or goal. Professionals who are skilled in data analytics are adept at conducting experiments, testing hypotheses and making inferences from the data within their reach. They’re tasked with thinking creatively about solving problems and applying human judgment to business challenges in an increasingly automated world.

Sharpen your data analytics skills

Big data has transformed the ways businesses operate. As more companies recognize the sizable benefits they could reap by seeking candidates with data analytics skills, the future is only going to grow brighter for professionals in the field.

If you want to be counted among the job applicants with the data skills that 70 percent of business leaders hope to encounter, now is the time to act. As you continue to learn more about this in-demand field, you may realize that furthering your education could be beneficial. See how you could add to your qualifications by pursuing one of the following education opportunities at University of Massachusetts Global:

• Master of Business Administration in Business Intelligence and Data Analytics
• Graduate Certificate in Business Intelligence and Data Analytics
• Bachelor of Arts in Spatial Social Sciences

*Source: Burning-glass.com (analysis of 168,697 data analyst, data scientist and business intelligence job postings, Sept. 01, 2018 – Aug. 31, 2019)