Information Governance-Control Content Chaos

As today's enterprises begin to redefine their infrastructures and management roadmaps to deal with big data, leading companies have begun to pursue a new vision of what their governance, risk and compliance (GRC) solution offerings should contain. Gone are the old-school strategies-adding storage and building mega-repositories to enforce policies in one place. In the new paradigm are "active information governance" approaches that leverage indexing technologies to discover, analyze and act in real-time on large volumes of data in their native environments.

The Core Information Governance Problem

The core problem to be solved in information governance is controlling content chaos. The volume, variety, velocity and complexity of enterprise information quite literally creates a world where managing data means keeping track of "millions of moving parts." The number of data sources being created, multiplied by the types and rate of change to support different use cases, has created a situation where data can no longer be moved to repositories and kept up-to-date. Almost uniformly, as soon as data is moved, it's out of date.

Information management vendors are beginning to respond to this new challenge by embracing an innovative philosophy about data governance. That is, rather than move subsets of data into a repository or application database to manage it, move management and governance to the data.

To support this philosophy, many vendors are buying and/or building new indexing technologies to search repositories and capture metadata about the content. Search is a great first step, but ultimately the challenge moves quickly to "what information needs to be captured so that we can act on what we find with policies that represent good governance?" There are many use cases to be supported, but these use cases can generally be categorized into six basic needs from a data index:

1. Identify—the location, source and volume of each piece of data. This is the typical search index;

2. Analyze—content patterns and trends along with the semantic relationships between sources;

3. Organize—data into sets of related information for further analysis and action;

4. Secure—access, retrieval and movement of critical pieces of data;

5. Govern—retention, deletion and compliance enforcement according to enterprise policies; and

6. Share—a secure, relevant subset of big data with business stakeholders requiring access.

The applications for a full index are broad in concept. Imagine a world where all users could get the information they require to optimize a business process or make a business decision faster, but without involving IT in a project to select and move data to support them. By leveraging an index of what is currently "active" in the big data environment, organizations can now eliminate the time-consuming, error-prone and tedious tasks of cataloging data and managing an ever-growing set of point applications and storage repositories. The data is created and managed where it lives while the business runs on the latest intelligence about the data.

Top 10 Strategies

We have a long history in IT of watching new categories of management technologies emerge. They always follow the same course... centralization, to mass anarchy, to distributed management solutions. We've seen it in databases, network/systems management, cloud-based services and CRM. And, we will see it again in information governance for big data.

The key to success for companies wanting to get out in front of information governance problems will be to implement an "active information governance" solution. These solutions will combine the same kinds of innovations that companies like Cisco brought to the network world with search and information intelligence technologies. The net effect will be an "always on" infrastructure capable of discovering, analyzing and acting on data in real-time. Companies looking to implement this approach will need to employ 10 new strategies for embracing the realities of information governance for big data:

1. Understand your data topology—holistically across the enterprise: how much; where; who owns it; and what value does it provide?;

2. Employ real-time indexing of the enterprise—to keep track of the many changes in state;

3. Store the intelligence about your data—to provide knowledge when it's needed that's accurate and up-to-date;

4. Create an information intelligence service center—armed with data analysts, business analysts and governance analysts that work as teams to balance volume to value;

5. Employ change management disciplines to stay current—that keep up with new forms of data and new business requirements;

6. Become proactive in deploying policies—for securing data, storing data, sharing data and enforcing compliance;

7. Clean up the mess—because nothing gets in the way more than the globs of data that remain in our enterprises that no one ever uses;

8. Define data life cycle and retention policies—to manage data as an asset;

9. Tier your access—to enable relevant data to be closer to the users and devices that are local; and

10. Educate the organization on the value of good governance—because, like most disciplines, it's less about control and more about raising the intelligence and health of information.

It's safe to say that the view of big data, governance and "indexing technologies" is evolving. As organizations begin to rely on indexes for more than enterprise search, all of the issues associated with speed, reliability, comprehensiveness and the ability to support multiple application use cases will begin to dominate the data governance discussion.

Big data—the source of so much content chaos—has pushed organizations into embracing information governance as a strategic priority. Once relegated to the IT and records management teams, information governance now impacts all areas of

a business. Embracing active information governance can cure the big data headaches across an organization including e-discovery and regulatory investigations, records management, and storage optimization—rather than simply treating the symptoms when new use cases occur. The result is a properly balanced, strategic approach that can deliver solid benefits for the entire business.