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The Data Analytics Skills Employers Are Seeking Most

In our modern economy, data is often acclaimed as the most valuable currency. There is an infinite amount of information stored within networks, storage and the cloud. The problem is most of it is unstructured and, therefore, not easily usable.

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It should come as no surprise, then, that data analysis skills are highly sought after by employers looking to harness the power of data. The ability to gather, analyze and interpret raw data allows organizations to make smart decisions, optimize workflows and gain a competitive edge.

Join us as we explore what data analytics entails and discover nine important skills for data analytics professionals with insight from Dr. Srikanth Mudigonda, director of analytics at SLU’s School for Professional Studies.

But First, What Does a Data Analyst Do?

Before diving in, it’s important to understand this role. According to Dr. Mudigonda, “Data analysts help organizations make data-driven decisions at the operational and strategic levels.” They accomplish this wrangling and examination of data to extract meaningful insights, identify patterns and come up with smart recommendations.

According to the Computing Technology Industry Association (CompTIA), the three stages of data use are:

Data analysts work across all three stages. Their job requires a combination of technical expertise, statistical knowledge and business acumen. Analysts are needed in all kinds of industries, including accounting, finance, banking, retail, marketing, real estate, healthcare, sales, wholesalers and more.

Nine Data Analytics Skills That are in High Demand

It should come as no surprise that there is a lot of technical knowledge and skill needed to work in data analytics. But “soft” skills are just as important to be successful in the field. In fact, it is this “Combination of conceptual, analytical, technical and communication skills that make data analysts such valuable assets in any organization,” says Dr. Mudigonda.

Let’s take a closer look at nine of the most highly valued competencies that employers are looking for when hiring data analysts.

Computer and Technical Skills for Data Analysts

To fulfill the duties of a data analyst, you’ll need to master a handful of specialized skills. Here are five that are becoming increasingly important:

1. Data Manipulation

Experts estimate that 90% of all data that is generated around the world is unstructured, meaning it follows no defined schema. This makes it very difficult to catalogue or sort.

Data manipulation involves cleaning up information, reducing redundancies and organizing it in a more accessible format. This step is crucial because it creates a usable data set that can be shared and analyzed.

2. Mathematics, Statistical Analysis and Modeling

Analyzing massive amounts of information is often complicated and requires mastery of math concepts like:

Using these kinds of techniques, analysts can uncover hidden patterns, make accurate predictions and extract valuable insights to benefit their organization.

3. Machine Learning

Machine learning is a branch of artificial intelligence that teaches computers how to forecast and predict outcomes without being programmed to do so. Computers are “trained” using huge volumes of unstructured data and highly engineered algorithms.

Data analysts can make use of machine learning techniques like:

This discipline requires a deep understanding of data science and software engineering. Data analysts who invest in developing these skills will be well-positioned to leverage this cutting-edge technology.

4. Proficiency in Programming Languages

Programming languages are essential tools that make it possible to effectively work with large data sets. Some of the most commonly used programming languages are:

As an analyst, being versatile and open to learning new languages and technologies will enhance your resume and could potentially increase your job opportunities.

5. Data Visualization

Once you’ve gathered information, compiled it into a useful dataset and analyzed it thoroughly, it’s time to share your findings. Turning raw data into a compelling argument or clearly laid out narrative can be tricky.

That’s why analysts use their data visualization skills to create visual models and representations of their work. Examples of data visualization could include:

Data analysts often use visualization tools like Tableau, Power BI, Google Charts and Microsoft Excel, so becoming familiar with these programs could help you be a competitive job candidate.

Communication and Organization skills for Data Analysts

The best data analysts have a solid set of soft skills — the kind of skills that aren’t specific to any one job — to complement the technical competencies described above.

Here is a look at four important qualities that help data analysts do their job effectively:

6. Strong Written Communication

You may be surprised to find that data analysts actually do a lot of writing. Analysts should be strong communicators who can produce clear and concise insights. They are often tasked with laying out their findings in reports, emails, white papers, case studies and other documents.

Data analysts are also responsible for documenting their processes and methodologies. Keeping accurate records enables knowledge sharing, reproducibility and transparency.

7. Public Speaking

Telling stories with (and about) data requires verbal communication and presentation skills, especially when delivering information to non-technical audiences. Many data analytics jobs require analysts to share their findings and recommendations on a regular basis. That means public speaking, attending meetings and presenting are essential parts of the job.

8. Problem Solving

Data analysts are frequently tasked with identifying opportunities for improvement and solving existing problems within an organization. This requires careful consideration, objectivity and creativity.

Critical thinking skills are crucial for making informed decisions. Data analysts must be able to apply deliberate and ethical evidence-based strategies to any given situation.

9. Collaboration

The ability to collaborate with executives, business leaders, colleagues, clients and other stakeholders across the business is a key skill for data analysts. They often work in teams to collect and process information, establish key performance indicators (KPIs) and make smart recommendations for business growth.

Relationship building and interpersonal competencies are important for this role. Data analysts often must rely on other departments and individuals within their company to provide data in a timely manner — and also need to understand the audience for their reports.

Become the Data Analyst Today’s Organizations Need

As organizations mature in their use of data and advanced AI tools, there is a growing need for trained and ethical professionals who have honed the skills listed above, Dr. Mudigonda says. “Companies need analysts to stay informed, make data-driven decisions and stay competitive in the market.”

Perhaps you already possess a handful of the soft skills outlined in this article, and all that’s missing is a specialized set of technical competencies.

Look no further than Saint Louis University’s master’s in analytics degree. As part of the School for Professional Studies, the program was built for busy professionals like you, with online and hybrid options broken down into eight-week courses.

Learn more by exploring our Master of Science in Analytics program today!

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