Data Analyst: A Future Proof Career Option [2022 Career Guide]

Abstract

That's why we're giving you a sneak preview into the world of data analysts! Who are data analysts, what do they do, where do they work, what is their earning potential and much more! What is Data Analytics? Data analytics is the process of analyzing data to extract useful information. The process of analyzing data typically moves through five iterative phases: Identify the data you want to analyzeCollect the dataClean the data in preparation for analysisAnalyze the dataInterpret the results of the analysis Data analysts use a variety of tools, including Excel, SQL, and Tableau, to examine data. Here's what many data analysts do on a day-to-day basis: Gather data: Analysts often collect data themselves. Interpret data: Interpreting data will involve finding patterns or trends in data that will help you answer the question at hand. Some of the most common tools in the data analytics industry include: Microsoft ExcelGoogle SheetsSQLTableauR or PythonSASMicrosoft Power BIJupyter Notebooks Data Analytics Job Types Types of data analysts As advancing technology has rapidly expanded the types and amount of information we can collect, knowing how to gather, sort, and analyze data has become a crucial part of almost any industry. People who perform data analysis might have other titles such as: Medical and health care analystMarket research analystBusiness analystFinance analystsBusiness intelligence analystOperations research analystIntelligence analyst As for the technical parts of data analytics, computer scientists and engineers can work as data engineers, IT systems analysts, and data architects, helping structure data and put it to full use. Related Online Courses Business Analytics by University of Pennsylvania Marketing Analytics University of VirginiaGoogle Data Analytics by Princeton UniversitySupply Chain Analytics by Duke University & University of Pennsylvania Data analyst technical skills Database tools: Microsoft Excel and SQL should be mainstays in any data analyst's toolbox.