Data cleansing tools can save you tens of thousands of dollars in unnecessary expenses and help optimize your business practices, then it is worth the expense. With the growth and emergence of a number of data cleansing software tools available on the market, it’s important for those shopping for high quality software to have a well-rounded perspective of what is available.
There are several things you should look for when evaluating data cleansing tools:
- High match accuracy when performing data cleansing tasks and functions
- Ability to link records efficiently and at a high speed without compromising accuracy
- Ease of use for the business user
- Affordability
Leaders in the field of data cleansing tools provide products and services that are rated very well by users.
Ease of Use: How user-friendly is the software? Is it easy enough for a basic business user to learn, or does it require significant knowledge and technical expertise to use?
Match Accuracy: This is one of the most important considerations when purchasing data cleansing tools. Having correct, updated information is one of the reasons data cleansing tools are required in any business toolkit. The software should also be able to detect instances of incorrect or duplicate data. When your data is accurate, business processes improve significantly.
Price: This is often determined by your particular organization’s business goals and size. There are data quality companies out there that offer an affordable option that won’t break the bank. Many companies offer varying levels of specialization that may not be required for your specific business. Understand the amount of data you’re working with and what your specific needs are.
Speed: This is also a critical factor to consider, especially when your company may have deadlines to meet.
Training/Implementation Time: How long will it take for a user or users to learn how the data cleansing software works? Depending on the project where the software will be used, the speed of implementation could be a major factor in the decision process.