A data analyst is a problem solver who prepares and analyzes data to provide organizations with insights that help them make better business decisions. If you’re interested in a tech career involving both technical skills and interesting challenges, a career in data analytics may be a perfect fit for you.
Data analysts collect, organize, and analyze data sets to help companies or individuals make sense of information and drive smarter decision-making. While all types of analysts conduct research to identify patterns and trends, data analysts leverage their technical skills — such as scripting, data blending, data visualization, and statistical programming languages — to help translate high-level business problems into well-informed potential strategies and solutions.
“A data analyst is someone with knowledge of Structured Query Language (SQL)/NoSQL, data presentation, and visualization languages who understands machine learning and data science, including statistics, math, linear algebra, and data structures,” says Chris Mattmann, chief technology and innovation officer at NASA Jet Propulsion Laboratory, and an adjunct research professor who teaches data science and big data at the University of Southern California. “A data analyst leverages these skills to apply to real-world structured and unstructured data sets to answer challenging business problems.”
- Business intelligence analyst: analyzes products, markets, or trends to assess market strategies
- AI analyst: analyzes data by leveraging machine learning models
- Data quality analyst: analyzes the quality of data that organizations use for decision making
- IoT data analyst: analyzes data collected from Internet of Things
- In addition to generating compelling insights from data, analysts offer data-backed scenario plans to help companies determine the risk level of different decisions.
- Descriptive: uses data mining for business intelligence
- Diagnostic: mines data anomalies to understand why something happened
- Predictive: makes forecasts based on data
- Prescriptive: focuses on data optimization and simulation
- Cognitive: combines data with artificial intelligence (AI)
“As most if not all departments in an organization can improve their performance and services with data analytics, professionals in this role have the capacity to advance company performance overall,” notes Kushner.
