Setting up processes and rules to avoid issues in siloed data sources in the first place should be put in place. Reducing free-form data entry where possible and having the same selection choices to help regulate the data entry can be a huge first step. For example, GA, Ga. and Georgia are all the same to us but are not considered the same when computationally comparing an address. Identifying a cross-functional team to plan and determine the rules is essential for success. The data needs to conform, but it also needs to make sense to those who capture and use it. Consider not only the quality of the data but also the intended consumers of that data. Use inline analytics to enrich and reduce errors during data entry, for example, consider a drop-down instead of allowing free-form entry. This would guarantee consistency. Keep your eye on the goal. Ultimately, you are doing this to save money and enhance customer analysis, customer communication and relationships.