You likely want to become−or remain−a data-driven business. Customer data appears to be constantly flowing through your organization, so it seems like you’re already on your way to being data-driven, right?
But red flags may arise when you take a closer look at your data. Your data sets could be rife with duplicate entries, inconsistent formats, and incomplete information. To activate your data’s full potential, you need the right data preparation techniques.
Evaluate the current state of your customer data landscape. Profiling can help you spot duplicates, incomplete values, and anomalies. Then you can transform data by standardizing formats and enriching it with additional attributes for a more complete customer record. The end goal would be to prepare your data for larger initiatives, like a single customer view (SCV) across your systems.
Data quality is the mechanism for successful data preparation. In addition to profiling, standardization, and enrichment , data quality ensures you provide accurate information for business use. Matching can identify duplicate customer records, and effective monitoring means continuous insight into the state of your data. These strategies can help you build a trusted source of customer data.
To learn more about the relationship between data preparation and data quality to bring your organization along, consult this whitepaper, “Building a business case for data quality."Get the whitepaper