You may have heard of big data in some form — machine learning, cloud computing, predictive analytics, and more. Big data and data analytics continues to redefine nearly every industry, particularly as organizations of all sizes across every field look to adapt to life in the wake of the COVID-19 pandemic. As a result, data analysts are in high demand — and this field is expected to grow exponentially in the coming months and years.

Here are 12 skills that you will need to pursue a career in data analytics and data science:

1. Research

If you hope to become a data analyst, then you will require a comprehensive understanding and proficiency in research and development. You should know how to research specific information, evaluate academic studies, and develop unique strategies for your project. Understanding where to find high-quality, reliable, and factual information is necessary when you work in the data analytics field.

2. SQL

Almost all data analysts use Structured Query Language, more commonly referred to by its initialism, SQL, on a day-to-day basis. Essentially, SQL serves as an advanced computing tool to input and process large amounts of data. It works more efficiently than a typical spreadsheet software, and no matter what job you take in the data analysis field, you are likely going to need to be familiar with SQL.

3. Microsoft Excel

Widely used by professionals across business industries, data analysts should also be well-versed in Microsoft Excel, a spreadsheet software offered within the Microsoft product suite. While most data analysts are skilled in working with other computing tools, such as SQL, an expert understanding of Microsoft Excel will help you, as a data science professional, work with people in all fields and at all skill levels. .

4. Data Wrangling

Data wrangling is the process of converting raw data into a more widely used format. For example, as a data analyst, you may take raw data and convert it into a Microsoft Excel spreadsheet for your clients to easily read and interpret the datasets. To further assist with data wrangling, familiarize yourself with Python, a tool used to clean and package data for your organization or client.  Big data and data analytics continues to grow, especially as more businesses prioritize data-driven decisions. Each dataset you analyze for your organization or client will require a different data wrangling technique to leverage and interpret the data effectively. Keep this in mind as you embark on or develop your career in data analytics.

5. Data Prep

When you’re working as a data analyst, your daily to-do list will frequently include data prep. Often the first step involved in leveraging data, data prep requires you to compile data from your databases and break it down into easily readable, interpretable, and understandable reports. You will often need to complete data prep before you move onto the next step — data visualization.

6. Data Visualization

As a data expert, you probably love looking at the numbers and crunching the information to better understand a specific scenario. However, we’re all unique and process information differently — that’s where data visualization comes in. Data visualization requires analysts to process and compile data visually for the average reader. To create visualizations, you will often convert and present your data with graphs, charts, and infographics for your clients to easily digest and understand.

7. Data Management

In addition to collecting data and generating reports, you also may be responsible for data management. Data management is the process of collecting, maintaining, and storing data securely over time for your clients as they develop data-driven predictions and decisions. Your clients may ask you to update your datasets with new information, thus requiring you to be familiar with specific queries and programming languages.

8. Statistical Programming Language

Depending on your data analysis role or position, you may not only have to understand many programming languages, but you may be required to become an expert in a specific language. We previously discussed Python as a tool used in data wrangling, but data analysts should also understand R, another programming language. These programming languages allow you to evaluate large batches of data in an efficient manner for your company or client to leverage that data as quickly and effectively as possible.

9. Machine Learning

Unlike studying a programming language or improving your data wrangling skills, machine learning is not necessarily a required skill if you want to work in data analytics. However, experience with machine learning can help you become a more attractive job candidate in a competitive market. Machine learning uses automated technology and artificial intelligence for predictive modeling and analysis. Based on the data sets, machine learning can, quite literally, identify patterns, accelerate business success by reducing manual efforts, and provide unique findings for your team to make data-driven decisions. When you know how to create an effective machine learning model, you will differentiate yourself in a growing and high-demand field that is sure to see an influx of job candidates.

10. Problem Solving

Most professionals, regardless of the industry they are working in, need to be adept and innovative problem solvers when presented with unexpected challenges. Data analysts are no exception. When presented with a data collection challenge or if your client is struggling to leverage their data appropriately, you’re expected to develop a creative solution that prioritizes accuracy and efficiency.

11. Public Speaking

Most data analysts imagine themselves sitting in an office setting, pouring over the data that they have collected, and compiling it into reports and visualizations for others to grow and improve their businesses. You may not have fancied yourself as a public speaker, but data analysts have to do a surprising amount of public speaking and presenting. In many cases, you will present and showcase your data to an audience — in person, not simply via email or PDF. Further differentiate yourself as an attractive candidate to prospective employers by becoming a skilled public speaker who knows how to present data to a group with optimal impact.

12. Project Management

As you oversee the collection of data and manage a variety of roles to accomplish a collective goal, a thorough understanding of project management will keep you and your team aligned and informed. Project management is known as the process of leading a team towards accomplishing different milestones to complete an initiative on a timeline. This process often includes a variety of meetings with your teammates to discuss milestone statuses, challenges, and other items that may arise throughout the project. As a data analyst, project management allows your team many opportunities to ensure the data and statistics needed by your organization or client are being collected appropriately and evaluated effectively for the desired outcome.

To develop your skills in this growing field and set yourself apart as a top candidate, consider pursuing a degree in data analytics with Johnson & Wales University. At Johnson & Wales University, we offer an online master's degree program in data analytics that provides you with the in-depth expertise you need to catapult your career in data analysis and data science.

For more information, complete the Request Info form, call 855-JWU-1881, or email onlineadmissions@jwu.edu.