The erwin, Inc. premiere of erwin DG at the DATAVERSITY® Data Architecture Summit 2017 marks a new approach to tackling the practice of discovering, understanding, governing and socializing data. That strategy, dubbed Data Governance 2.0, puts the focus on making Data Governance everyone’s business, in order to fully leverage data for strategic advantage and remove as much risk out of the systems and processes associated with that data.
Pivoting Data Governance from an IT-centric “custodian-oriented” service, to one where every member of the business is invested in and accountable for data use, is part of erwin’s overall vision. It has become a more prevalent way of thinking among its customers, too. A few dozen are currently participating in its beta program.
With erwin DG, the company eschews the concept of using a single interface, fairly technical in nature, in favor of role-based and role-aware access into the tool. This provides a meaningful interface to various enterprise functions spanning business and IT. “The concept of data in context is key to Data Governance 2.0,” says Danny Sandwell, erwin product marketing manager.
Consistent views of data relevant to individuals’ unique roles make it possible for the same “data pie,” to be presented in multiple ways, aligning to the perspective most meaningful to the particular user. That perspective includes enumerating applications, processes, data flows, access request procedures, and quality assessments for that data consumer role to refer to and abide by. Similarly, what a particular user adds to that data pie will be transformed for use by other roles, so that other individuals can view that “slice” in the context that matters to them.
Built-in linkages and rigorous workflows between different roles for easy and effective collaboration is another capability to empower erwin users to better leverage and protect data across the organization. Together, role-aware access to well-managed data and well-defined workflows enables the culture of Data Governance to be woven into the fabric of the enterprise.
An All-Inclusive Take
Today, of course, data can be composed of relational, unstructured, on-premise, and cloud-based data assets – and for Data Governance to succeed it has to support them all, along with well-documented business rules. erwin’s any data, anywhere (Any2) approach is a key foundation here.
“If Data Governance extends to only 25 percent or so of the data available to people in the organization, the impact is minimal and the ability to squeeze risk out of endpoint decisions is not particularly impactful, because a lot of that risk is built into that other 75% of data,” Sandwell says.
Any2 provides the means for Data Governance to go beyond supporting just the easy data sources, like traditional managed relational database stores, to a world of Big Data volume, variety and velocity.
“All sorts of data is equally important – to the business data is data, whether in a database or streaming XML file that gives them data points every nanosecond, which is the reality of the Internet of Things,” he says. “For data scientists or business analysts or anyone else trying to bring internally owned or externally purchased data together and use it for decision-making purposes, they have to be assured that it’s trustworthy, of high quality and well understood. That way they don’t misapply it in algorithms in their jobs.”
The new erwin DG also is a cornerstone of an overall company vision that focuses on bringing together different disciplines and technologies to help organizations be more agile, cost-efficient and effective in planning change and understanding the landscape of their enterprise from a data perspective. To that end, its Data Modeling, Enterprise Architecture, and Business Process Modeling solutions link together to feature in the Data Governance experience.
Sandwell notes that integrating each of these erwin solutions brings a special value to supporting a full Data Governance environment. That includes boiling things down to atomic data elements and descriptions of data assets; visualizing what systems, reports, data models, and others these assets map to; and, understanding how they are affected by processes and applications in motion. For instance, leveraging Enterprise Architecture to attach core data elements to things like goals and strategies, and connecting the dots about the systems and applications that actually manipulate and serve up that data, delivers an extended picture that is valuable to Data Governance as it relates to planning and analyzing change.
“A big part of Data Governance is not just understanding what you have and applying rules, but to plan and analyze change. A lot of that is about what is the impact of a specific data element as it spreads across the enterprise,” Sandwell says.
Say for example, a new requirement leads to considering a data element change. Because erwin has brought together multiple disciplines as part of an integrated Data Governance ecosystem, it has the capability out of the box to integrate different artifacts around that data element together in a meaningful way.
“We put the power of data impact analysis into customers’ hands at a level the competition can’t approach,” he says, incorporating different disciplines to provide users the means to understand where the change would have to be accounted for, what that would cost, and whether from a cost-benefit analysis perspective it’s worth making. That is, does it deliver mission critical value or is it merely a nice-to-have that brings with it too much risk?
Connections and Subscriptions
In addition to integrating with erwin’s own Data Modeling and Enterprise Architecture applications, erwin DG also integrates with third-party solutions. erwin Collector, for example, provides a way to identify other data sources, and map and integrate to them. “There are all sorts of other enterprise solutions that Data Governance needs to be linked with,” Sandwell says, from something as simple as service desk offerings to Enterprise Governance, risk and compliance software.
That’s integral to the notion of a corporate governance framework, says Jaime Knowles, product manager at erwin:
“Data Governance is not just about understanding business logic and data dictionaries but how the organization as a whole is using its data and where is the risk in the organization,” he says.
It’s one thing, for example, to solely lock down data in a database for regulatory or security reasons, but “if you have an application firing out reports on the back-end with no governance on that, you’ve missed the mark,” Sandwell says.
“True Data Governance has to cover more than just understanding the picture of the data,” adds Knowles.
Erwin DG is a SaaS solution. Enterprises pay monthly fees for two different license levels. Contributor licenses are for those in the organization that will be doing the heavy lifting, such as Data Stewards or business or data owners, Knowles say. Reviewer (or consumer) licenses, available for a considerably lower fee are for everyone else in the organization. After all, in Data Governance 2.0, everyone is a data stakeholder.