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\u2019t. For some companies, it\u2019s not worth cleaning data errors like sloppy punctuation when they don\u2019t 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.