When you take a look at the condition of the data — how well it’s meeting your needs based on metrics like accuracy, consistency and completeness — you’re looking at data quality. And, as with most things, you want your data to be high quality so you know you’re generating the most useful, helpful results possible. When gathering data, it’s essential to ensure those data accurately and fully represent the information you’re attempting to capture with them. Those data need to be reliable and consistent so you’re sure the conclusions you’re drawing from them are precise and correct.‎

Whether you’re reading statistics in the news or you plan to work with data one day, understanding data quality can help you better judge everything from the integrity with which a study was conducted to the metrics you’ll use as you set up a large research project. People often make big decisions based on data, and knowing how valid, accurate and applicable those data are can influence those choices. When data aren’t high quality, they don’t provide the right insights — and the right insights are truly what you need in order to avoid poor decision-making and other unfavorable outcomes. When you learn about data quality, you become better at assessing those data and utilizing them, and the choices you make — or the software you’re developing for data analysis — will have more integrity as a result.‎

Jobs that involve working closely with data will have you assessing data quality on a regular basis. You might work as a data quality specialist who defines and measures data quality standards for a company. Or, perhaps you’ll find a position as a data governance and quality analyst who integrates data into different systems to generate new insights about their meaning and relevance. With new knowledge about what data quality is and how to assess it, you’ll be better prepared to enjoy these and other careers.‎