In The Future of Data Governance, How the Analysts got it Right, Collibra CTO, Stijn Christaens analyses Gartner’s 2009 and 2015 research on the emerging Information Stewardship market.
Their principle finding:
The wide range of responsibilities that data stewards must carry can only be supported by a horizontal stewardship platform.
In his post, which is worth reading, Stijn discusses how Collibra embodied this vision through the delivery of the world’s leading Data Governance platform – a horizontal platform built from the ground up to automate and support numerous common data stewardship functions, for example:
- A data helpdesk for issue management: Often users discover the data they want to use is unfit for their purpose (it turns out the quality is too low, the data is not granular enough, …). Cue the steward who has to manage these incoming data issues (triage, root cause analysis, escalation, …).
- A business glossary to centralize and coordinate shared meaning: We don’t always understand each other, especially when we have to move out of our daily business context (e.g., sales) to interact with our colleagues in their business context (e.g., support). Translate this into KPIs, metrics, table names, code, and you can see how stewards often serve as keepers and catalysts of shared understanding (such as uncovering legacy meaning, approving a shared metric, tracking new data development, understanding traceability and lineage, the list goes on.)
- A data valuation console to keep track of the actual (and present and future) value of your data: Not all data is created equal. And, while we live in the age of the data explosion, only a small percentage of that data is actually valuable, especially over a prolonged period of time. Stewards help identify value and prioritize activities so that valuable data can be managed appropriately (valuation criteria, value dashboards, impact on business, …)
While Gartner predicted the emergence of the data governance centre, their research to date has focused on the historical IT vendors postioning of fragmented data management capabilities – such as MDM, Data Quality, Data Integration and Metadata Management.
This may mean that data architects, and other decision makers, looking for applications to support data governance may paint themselves into a corner by selecting a solution limited to one of these research papers The limited focus of the metadata tools, for example, means that they cannot be extended to support additional stewardship use cases – such as the data help desk, data quality governance, reference data governance, report certification and many more.
There is, at date of reading no Gartner Magic Quadrant, for the Data Governance or Data Stewardship platform.
Forrrester’s research echoes the earlier Gartner finding – that a horizintal data stewardship applicaiton is a business essential -and profiles companies delivering on this vision – what Forrester calls data governance 2.0
In the Forrester Waves we see newer, more innovative vendors that achieve the Gartner and Forrester Data Governance 2.0 vision displacing established rivals that have what Forrester calls a Data Governance 1.0 (IT project driven) approach.
The advantage that these newer vendors have is that they have designed from day 1 to solve the enterprise problem, rather than having to try to cobble together multiple applications and acquisitions to try and build some kind of cohesive whole.
Collibra, for example, was designed from day 1 to deliver:
- a core integrated governance platform so no stewardship application ever has to feel the cold of a silo
- out-of-the-box stewardship applications so any organization new to the governance game can hit the ground running
- a configurable operating model so complex or large companies can adapt and extend the stewardship applications to their own processes and needs
- an integration capability so stewards can tap into any and all data management and other toolsets already existing in the company.
The future of data governance is now!
Companies that approach the challenges of data governance in the right way, and select appropriate tools, will build an understanding of the information assets that will empower trusted analytics, ensure operating effectiveness and support new data-driven approaches to revenue generation.
This is not the time to paint yourself into a corner.
Ask yourself three questions:
- Does the technology choice I am making provide robust support for my current (first priority) use case? It is important that this initial case is strong and delivers value
- When I need to (next week, next month or next year) can I easily add additional use cases? What use cases are supported and how easily can they be extended? Data is pervasive and over time the Data Governance platform may need to support master data management, big data, BI and even compliance programs. A wide range of possible use cases means that you can support multiple stakeholders and coordinate and manage data issues and risks to enable numerous business projects.
- What is your engagement model? Data governance in a large environment is complex. Different stakeholders have differing expectations, different needs and competing priorities. many of your most important users will be part time and pressed for time. How will you minimize the impact of data stewardship on each person – through automation, through consistent interfaces for different tasks, through meaningful reporting and management controls, and through re-use of existing technical data management artifacts such as data models.
Technology is not a silver bullet. Implementing a data governance platform does not mean that you will have data governance.
However, the the right data governance platform will help to manage the complexity that is the reality of corporate EIM environments – making data governance practical and visible.
learn more about Collibra with the Collibra datasheet, or contact us for a demo on +27114854856