Data Quality issues can waste time and reduce productivity. They can also damage customer satisfaction, or even result in penalties for regulatory noncompliance. Poor Data Quality wastes time and energy, and manually correcting a database’s errors can be remarkably time consuming and also conceal opportunities from a business, or leave gaps in understanding its customer base.
Organizations do not communicate or define their data expectations when receiving data from other sources. Few provide clear, measurable expectations about the formatting or condition of data before it is sent to them. Without communicating clear expectations, it is not possible to measure the quality of the data as it is received.
ripelogix Data Quality sets the stage for continuous delivery of data improvement by evaluating your data in operational and decision-making contexts to identify its value and focus on what matters most. This is followed by IT and the business working together to continuously improve data. Here are the steps to follow:
