The Gartner Magic Quadrant for Data Quality Tools 2017 is out. One place to get it for free is at the Informatica site.
As data quality for product data is high on my agenda right now, I did a search for the word product in the report. There are 123 occurrences of the word product, but the far majority is about the data quality tool as a product with a strategy and a roadmap.
The right context saying about the product domain is, as I could distil it based on word mentioning, as follows:
Product data is part of multidomain
Gartner says that the product domain is a part of multidomain support, being packaged capabilities for specific data subject areas, such as customer, product, asset and location.
Some vendors were given thumbs up for including product data in the offering. These were:
- BackOffice Associates has this strength: Multidomain support across a wide range of use cases: BackOffice Associates’ data quality tools provide good support for all data domains, with particular depth in the product data domain.
- Information Builders has this strength: Multidomain support and diverse use cases: Deployments by Information Builders’ reference customers indicate a diversity of usage scenarios and data domains, such as customer, product and financial data.
- SAS (Institute, not the airline) has this strength: Strong knowledge base for the contact and product data domains.
One should of course be aware, that other vendors also may have support for product data, but this is overshadowed by other strengths.
Effect on positioning
Multidomain brings vendors to the top right. Gartner’s metrics means that leaders address all industries, geographies, data domains and use cases. Their products support multidomain and alternative deployment options such as SaaS.
Product data focus can make a vendor a challenger. Gartner tells that challengers may not have the same breadth of offering as Leaders, and/or in some areas they may not demonstrate as much thought-leadership and innovation. For example, they may focus on a limited number of data domains (customer, product and location data, for example). This also means, that missing product data focus keeps vendors away from the top right positioning, which seems to be hitting Pitney Bowes and Experian Data Quality.
Product data will become more important, but is currently behind other domains
Gartner emphasizes that data and analytics leaders including Chief Data Officers and CIOs must, to achieve CEOs’ business priorities, ensure that the quality of their data about customers, employees, products, suppliers and assets is “fit for purpose” and trusted by users.
Organizations are increasingly curating external data to enrich and augment their internal data. Finally, they are expanding their data quality domains from traditional party domains (such as customer and organization data) to other domains (such as product, location and financial data).
According to Gartner, data quality initiatives address a wide variety of data domains. However, party data (for existing customers, prospective customers, citizens or patients, for example) remains the No. 1 priority: 80% of reference customers considered it the top priority among their three most important domains. Transactional data came second highest, with 45% of reference customers naming it among their top three. Financial/quantitative data was third, with 39% of reference customers naming it. The figure for product data was 34%.
In my view, the 34% figure is because not all organizations have high numbers of product data and have major business pains related to product data. But those who have are looking at data quality tool and service vendors for suitable solutions.
Liliendahl on Data Quality 