There are thousands, if not millions, of ways to accumulate data for use within your organization. But collecting that data is only the first step. It’s important to think about what to do with the hordes of information you have at your fingertips. Some questions to ask yourself:
- What is the quality of this data?
- Who in my company would have a problem with data inconsistencies?
The reason these questions are important is because data has the uncanny ability to be and stay “dirty”. Each year volumes of data grow, and this just compounds an already existing problem. Making it worse are (human) keying errors, duplicate data, and the lack of governance (human and machine).
Each data point you’ve captured, whether it be an internal source, an external source, or from a device is unique in its own way. It’s more useful to you if it is cleansed and standardized. This way, you can tell an accurate story of how information is impacting your business. Tackling these issues must be a priority if you ever want to use that data for accurate reporting and analytics.
Cleansing and standardizing large data sets can be a staggering task, especially if you approach data quality manually, without supporting technologies in place. Even though the potential for data quality issues is high, many organizations ignore the need to maintain big data integrity.
So for hints on how to address the impact of dirty data, and how you go about fixing it, we’ve developed an e-book called “Getting Started with Data Quality.”
With good data quality, you can increase the value of information capital; enable faster, smarter decisions; and make it easier to achieve regulatory compliance. Our self-service model can help with that. Read the e-book, and then download the software – it’s that easy.
We would love to know what you think.