Data quality strategy through Datactics

The company is a pure-play data quality vendor, offering the full spectrum of data quality functionality, from data profiling through to data cleansing, merge/matching and data enrichment. It is particularly aimed at empowering business users to take control of data quality rather than delegating this to the IT department. Extensive use of artificial intelligence techniques underpins features such as automated business rule suggestions, rapid matching of records and predictive insights. This last feature is unusual and interesting: as well as highlighting data errors and anomalies, the product analyses patterns of errors and endeavours to identify the root causes of data errors based on previous experience; it even identifies how long a particular class of error typically takes to fix. The current product version, launched in mid-2023, is known as Augmented Data Quality (ADQ).

Fig 01 – Product Augmented DQ Platform

Customer Quotes

“Really easy to engage with you and I want to say we have really enjoyed working with you. It has felt like a proper collaboration where we have worked together to sort out any issues and you have been more than fair with us.”
NHS BSA

“The platform’s usability means our SMEs can now develop data quality rules themselves – extending the functionality to multiple regulatory requirements and broader data quality and governance applications.”
Danske Bank

“Excellent reliable product approved by users. Helpful and solution-oriented tech leads.”
Peer Insights review

As well as traditional data profiling, cleansing and record matching, Datactics ADQ enables business users to create a portfolio of data quality rules. The product itself uses artificial intelligence techniques to suggest likely data quality rules based on the patterns of data that it detects. Rules can be tuned and tailored, for example to establish threshold levels at which potential duplicate records can be automatically accepted or referred to human domain experts. The product’s user interface, substantially upgraded in the most recent software release, is role-based. So, for example, a data steward, an administrator and an end user may see entirely different interfaces and can create and work with different data workflows and data pipelines. Common tasks are made more productive via the use of wizards. Outliers are detected and alerts sent. The product can interface to data catalogue tools like Collibra, to master data management tools and data warehouse products such as Snowflake, as well as analytic tools like Tableau and Qlik. Dozens of connectors to source systems and applications are provided. The product is data domain agnostic, so as well as looking at the quality of customer name and address data the product can equally well be used to handle other data domains such as product, location and asset.

Fig 02 – Integrating Machine Learning Innovation

Data quality is a quite long-established software sector, and yet the issue remains a stubbornly difficult one to address. Only around one in three executives actually trust their data, a figure that has proved remarkably consistent in surveys by several prestigious organisations in recent years. One issue has been that the issue of data quality has frequently been delegated to the IT department, who are not in a position to deal with it properly. Software products that aim to engage business users are the ones that are most likely to make a dent in this thorny problem, and Datactics is a specialist pure-play product with a modern user interface that works pro-actively to suggest data quality rules and to support business workflow associated with data quality. ADQ is a non-disruptive product that plays well with existing data management tools such as data catalogues and master data management hubs. Its ability to explain why a particular data quality recommendation is made is useful and unusual, enabling trust to be built in the product amongst the business users.

The bottom line

Datactics is a pure-play data quality vendor with some innovative features and a complete set of data quality functionality. Companies wishing to empower their business users to improve their data quality should seriously consider this product.