The Gartner Magic Quadrant for Data Quality Tools 2019 is out. It will take you 43 minutes to read through, so let me provide a short overview.
Gartner says that “data quality tools are vital for digital business transformation, especially now that many have emerging features like automation, machine learning, business-centric workflows and cloud deployment models.”
The data quality software tools market was at 1.61 billion USD in 2017 which was an increase of 11.6% compared to 2016.
Gartner sees that end-user demand is shifting toward having broader capabilities spanning data management and information governance. Therefore, the data quality tool market continues to interact closely with the markets for data integration tools and for Master Data Management (MDM) products.
Among the capabilities mentioned is multidomain support meaning capabilities covering all the specific data subject areas, such as customer, product, asset and location. Interestingly Gartner continues to focus on customer as the one of several party data domains out there. In my experience, there are the same data quality challenges with vendor and other business partner data as well as with employee data.
According to Gartner, data quality tool vendors are competing to address shifting market requirements by introducing an array of new technologies, such as machine learning, interactive visualization and predictive/prescriptive analytics, all of which they are embedding in data quality tools. They are, according to Gartner, also offering new pricing models, based on open source and subscriptions.
The vendors included in the quadrant are positioned as seen below:
If you want a full copy of the report you can, against providing your personal data, get it from Information Builders here.
Liliendahl on Data Quality 