Data quality is important to any organization, regardless of data that you may have. You can be using data to run machine learning algorithms, run your sales and marketing or to run analysis on your customers and prospects. Depending on your data needs and your data tools there are different data quality providers. So what are they? And what purpose do they solve?

Data Appending  and Third Party Data Providers – There are many data providers in the market place that are used to either verify your data or append data to your existing records. They typically are split between B2B and B2C and have different match rates. The match rates can be as low as 30% or as high as 70%, therefore, it is advisable to use multiple data providers in order to increase your match rates, you may also use a third party data broker, such as StrategicDB that can help source data from multiple sources and help fill in manually missing data to improve match rates. Some examples of B2B Company or Contact Data appending includes: Oceanos, ZoomInfo and D&B. Some examples of B2C data appending services includes Experian and Melissa.

Data Cleansing Libraries for R or Python: For machine learning, there are data cleansing libraries that you can use to automatically format and clean up some of the data. Typically they are fairly basic in what they can achieve. For example, if you have different data formats they can convert it into the same format or if you have data in different fields you can merge them into one and so on. They may even find duplicates or use fuzzy matching logic which is at a basic level a good first step to de-duping. However, they will not solve the issue of standardizing your industries which are not going to be caught by fuzzy logic or deal with complex de-duping rules.

De-duping Tools: There are many solutions in the marketplace that will find duplicates or stop duplicates from being created in your system. Some of the providers include: DupeCatcher, Cloudingo, Demandbase, Ringlead, Reachforce and WinPure. These providers are often focused on only one or two tools, typically Salesforce. They also have limitations on how they identify duplicates and how they establish master/merge. The solution that StrategicDB has come up with their De-duping tool caters to ALL systems and types of data and uses your own business rules to identify duplicates and establish the surviving record.

Data Governance Tools: Finally there are tools that will help with data security and data governance they are typically enterprise level such as Oracle Data Quality, IBM, SAS Data Management and Logstash. These tools are generally catering to large scale organizations and come at a very high cost. You can implement your own data governance just by simply coming up with data rules, user’s permission and establish processes.

Regardless of what data quality tools you use or plan to use, remember, to understand the pros and cons of each tool, to conduct cost/benefit analysis and to find the right solution for your business. There is also no tool in the marketplace today that will solve all data problems including data standardization/normalization, the correctness of your data, having outdated data or a solution that will make your data 100%. Therefore, you may want to consider opting in for a data cleansing services instead.