1 Prioritize the task. Cleaning data can be costly and time-consuming, so your first step should be figuring out which data is mission-critical and which isn’t. For some companies, it’s not worth cleaning data errors like sloppy punctuation when they don’t get in the way of business objectives. 2 Involve the data owners. Ask the business units that own the data for help defining precise rules for what constitutes dirty data. That includes figuring out in advance whether 98 percent clean is good enough, or whether 100 percent is required or affordable.3 Keep future data clean. Put processes and technologies in place that check every zip code and every area code.4 Align your staff with business. Make sure you have IT people working on the ground with business units to make necessary changes in the data and relabel wrongly tagged inventory. Related content BrandPost Why CISOs Are Looking to Lateral Security to Mitigate Ransomware How to fight ransomeware attacks with lateral security By VMware Mar 27, 2023 2 mins VMware Cloud Security Feature State of the CIO, 2023: Building business strategy Despite a focus on core modernization and transformation work, 2023 State of the CIO respondents say CIOs are playing a strategic leadership role with impact that transcends IT. By Beth Stackpole Mar 27, 2023 11 mins CIO Business IT Alignment Digital Transformation Analysis Why data leaders struggle to produce strategic results A recent Gartner survey of data and analytics leaders found that fewer than half think their teams are effective at providing value to their organizations. Here’s how to change that equation. By Thor Olavsrud Mar 27, 2023 8 mins Chief Data Officer Data Management IT Leadership BrandPost How Infosys and Tennis Australia are harnessing technology for good By Veronica Lew Mar 26, 2023 6 mins Infosys Podcasts Videos Resources Events SUBSCRIBE TO OUR NEWSLETTER From our editors straight to your inbox Get started by entering your email address below. Please enter a valid email address Subscribe