7 In-Demand Data Analyst Skills to Get You Hired in 2024 | Coursera
Each year, there is more demand for data analysts and scientists than there are people with the right skills to fill those roles [1]. In fact, according the US Bureau of Labor Statistics the number of job openings for analysts is expected to grow by 23-percent between 2021 and 2031, significantly higher than the five percent average job growth projected for all jobs in the country [2].
1. SQL
Structured Query Language, or SQL, is the standard language used to communicate with databases. Knowing SQL lets you update, organize, and query data stored in relational databases, as well as modify data structures (schema).
2. Statistical programming
Statistical programming languages, like R or Python, enable you to perform advanced analyses in ways that Excel cannot. Being able to write programs in these languages means that you can clean, analyze, and visualize large data sets more efficiently.
3. Machine learning
Machine learning, a branch of artificial intelligence (AI), has become one of the most important developments in data science. This skill focuses on building algorithms designed to find patterns in big data sets, improving their accuracy over time.
4. Probability and statistics
Statistics refers to the field of math and science concerned with collecting, analyzing, interpreting, and presenting data. That might sound familiar—it closely matches the description of what a data analyst does.
5. Data management
Data management refers to the practices of collecting, organizing, and storing data in a way that is efficient, secure, and cost-effective. While some organizations will have roles dedicated to data management—data architects and engineers, database administrators, and information security analysts—data analysts often manage data in some capacity.
6. Statistical visualization
Gleaning insights from data is only one part of the data analysis process. Another fundamental part is telling a story with those insights to help inform better business decisions. That’s where data visualization comes in. As a data analyst, you can use charts, graphs, maps, and other visual representations of data to help present your findings in an easy-to-understand way.
7. Econometrics
With econometrics, analysts apply statistical and mathematical data models to the field of economics to help forecast future trends based on historical data. Understanding econometrics is key for data analysts looking for jobs in the financial sector, particularly at investment banks and hedge funds.
Ref: Coursera, Feb 6, 2024