data analyst skills.pdf
- 2. SQL 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. 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. STATISTICS AND PROBABILITY 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.
- 4. 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. ECNOMETRICS 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.
- 5. Tips for learning data analysis skills Set aside time to regularly work on your skills Learn from your mistakes Practice with real data projects Join an online data community Build your skills bit by bit Data analysts leverage these and other technical skills to help inform decisions at their organizations. Putting in the time and effort to learn these skills can set you up for a successful career as a data analyst. Here are a few quick tips for getting started: