In our last member survey, many people requested that we undertake more interviews with data quality technology providers in order to understand the latest innovations in the marketplace.

We are therefore launching a series of data quality technology interviews with vendors across the full spectrum of the data quality technology industry.

A relatively young company that has created something of a stir of late with their data quality governance message and SaaS delivery model is Clavis Technology, who have their headquarters in Dublin, Ireland.

To find out more we recently spoke with their CEO Garry Moroney, someone who is no stranger to the data quality technology sector.

Data Quality Technology Interview: Clavis Technology

Data Quality Pro: For the benefit of our readers Garry, can you please describe your background, this is not your first venture into the data quality marketplace is it?

Garry Moroney: I have been working in the data quality industry for over 10 years. In 2001, I co-founded a company called Similarity Systems – which pioneered the concept of a highly configurable data quality tool that could be used by data analysts to audit and cleanse any type of data.

Over five years, Similarity built a broad customer base of global companies. The company was acquired in 2006 by Informatica Corporation (Nasdaq: INFA).

I then spent a year as General Manager of Informatica’s data quality software division before founding Clavis Technology in late 2007 together with the former CTO of Similarity Systems, Chris McCauley.

Data Quality Pro: It's a number of years since the launch of Similarity Athanor. How do you feel the data quality market has changed - what innovations do you think organisations are now looking for?

Garry Moroney: The market has grown very substantially and continues to grow because the negative impact of poor quality data continues to increase as organisations strive for greater levels of automation, outsourcing and business intelligence.

In addition, the awareness of data quality as a major business inhibitor is now much more widespread.

The other important change is that large numbers of companies have now had experience with first initiatives to tackle data quality problems – and are looking at ways to do it better.

In terms of the standard maturity model – many large organisations have moved from “awareness” to “reactive” and are now at the “proactive” stage where they are looking at taking a much more managed and proactive approach to data quality.

Data Quality Pro: You state on the website that Clavis provides "Data Quality Governance Software" - how exactly does the relationship with Data Governance come into the solution?

Garry Moroney: Data Governance is all about defining and implementing policies and procedures and roles and responsibilities relating to data processes within the organization.

The stakeholders within the business must have control and be empowered to define and measure KPIs relating to data processes, for example; timeliness, quality, standards conformance, within and across business processes. They must also have the visibility as to how processes are working, have the information and tools to carry out effective root cause analyses and effect process improvement across all parts of the enterprise and end to end for complete data lifecycle.

Our focus is purely data quality, Clavis Data Quality Steward enables organisations to define, implement and manage policies, standards and procedures, metrics and responsibilities for processes that impact data quality.

Primarily these are processes where new master data is created - processes like new product introduction, product-market activation, customer/vendor onboarding etc.

Click to view full screenshot image

Data Quality Pro: Clavis claim to take a fundamentally different approach to data quality, namely one of preventative action as opposed to "inspection and correction". We've ironically just been writing about the need for more preventative solutions to data quality on our site, so how does your technology actually manage defect prevention?

Garry Moroney: There are three elements to our prevention approach:

1. Providing the appropriate data checks and assistance at the point where data is first created – to help the data creator get the data “right first time”
2. Providing realtime monitoring of data quality failures in a data creation process to enable the data administration/governance staff to efficiently identify issues and take action as they occur
3. Providing the metrics required for effective root cause analysis of where and why data problems are occurring in a process – to drive process improvement

Data Quality Pro: You're offering your data quality solution in a SaaS format, is this via online? How exactly is the SaaS format delivered?

Garry Moroney: Yes Clavis DQ Steward is typically hosted “in the cloud”.

This cloud based approach is key to our proposition of applying data quality controls wherever the data is first being created – whether that be at some far corner of the enterprise or even outside the enterprise by a customer or partner. As long as the user is connected to the internet then the appropriate data quality controls will be applied.

In addition collaboration and visibility are key to governance and our SaaS approach means that data quality rules and references can be collaboratively developed and shared.

Finally, data quality metrics and feedback are easily available to all – even business partners.
Increasingly third parties are involved in the data creation process as trading partners or business process outsourcing partners. To be effective, these 3^rd parties must be part of any data quality governance initiative.

We can also install Clavis in-house if an organisation requires this. However this obviously impacts the accessibility of the product to users outside the organisations firewall.

Data Quality Pro: The literature surrounding the solution implies that you manage business rules rather than data rules, what are the advantages of taking this approach?

Garry Moroney: To apply the level of granularity to make data quality controls really effective in ensuring data is “right first time”, then data quality rules must be based on business rules.

By this I mean that, in addition to basic data rules they must also include context - in terms of the process where the data is being used (e.g. new product introduction for product category A or customer onboarding for region B) and the stage of the process that the data is at– e.g. initial request, final sign-off etc.

Data Quality Pro: With regards to business rules, these can obviously span multiple systems, how does the Clavis solution approach this issue?

Garry Moroney: This is a core part of the Clavis value proposition. All data quality rules and references maintained in Clavis are accessed from multiple systems.

In Clavis all data quality controls are maintained in highly structured glossaries – the contents of a glossary are simply mapped to the data attributes of the particular system.

The integration then involves sending xml messages over HTTP to Clavis with the data attribute values. Clavis intelligently applies the appropriate data quality controls and generates error messages, supporting contextual help and where applicable, suggestions as to the correct value that should be entered. It also provides central monitoring on the level of data errors in a process at any time.

For widespread data collection tools like excel, webforms, pdf forms, we provide plug-ins to enable mapping to Clavis Glossaries from inside the application so users can integrate Clavis with new data collection forms with no technical input. But Clavis is also being used with SAP and other applications where some level of technical integration is required.

Data Quality Pro: What process do you follow in order to gather and maintain business rules as this is something that many organisations struggle to manage?

Garry Moroney: We believe that many organizations do not perform this well as the stakeholders in the business are not empowered to own, maintain and enforce the business rules appropriate to the processes they own.

Change requests and reporting requests are mixed with other IT priorities and it takes too long to effect business rules change and monitoring. This is one barrier Clavis will definitely overcome, time to value and time to effect improvement in data processes. We have a well developed methodology for the rules and supporting reference content development and roles and responsibilities.

Data Quality Pro: As mentioned, you make a number of references to data governance in the solution literature, if an organisation has a low maturity in this area do you also provide a methodology to help organisations develop capabilities in this area?

Garry Moroney: Clavis Data Quality Steward provides a framework for the implementation of data quality governance. Many organisations know they should be “doing data governance” but don’t know where to start. Clavis provides organisations with a highly actionable approach to data quality governance. Clavis is not about a “big bang” approach, it enables organisations to take small steps forward towards data governance with a focus on delivering immediate business value.

Data Quality Pro: In terms of conventional data quality tools, what sets Clavis apart?

Garry Moroney: Hopefully I’ve covered much of this above. But in a nutshell three things make Clavis Data Quality Steward fundamentally different to the more established data quality tools:

1. SaaS approach enables us to apply data quality controls in upstream highly dispersed data creation processes where data is provided by many people in many places via many different forms or applications
2. Our data quality controls are owned by the business stakeholder, are configurable to be context-sensitive based on a knowledge of the business process and the stage of the process where the data is being provided
3. Clavis DQ Steward is built around the three pillars of data governance – defined data quality roles and responsibilities, robust procedures (e.g. for creating/updating DQ controls or processes) and comprehensive metrics visible to all stakeholders.

Data Quality Pro: What will be your goals for 2009 - can you share any immediate plans for the future?

Garry Moroney: We are very excited about the positive feedback we are getting from users of Clavis Data Quality Steward. We already have sales presence and active partners in the United States. Our key aim for 2009 is to expand our team and our partner network to enable us to support the current demand and extend our presence into new markets and geographies. We also continue to invest in further development of our software and methodologies.

For more details of Clavis Technology refer to their website: http://www.clavistechnology.com

The next post in this series will feature an interview with UK based X88 Software.