Amid ongoing concerns over data privacy, ownership, and governance, technology leaders are playing a critical role in making data broadly available throughout the enterprise, while also ensuring compliance with an array of differing data regulations around the globe.
CIOs can take advantage of a holistic data management approach and new cognitive capabilities to increase data accessibility and control.
As data grows in complexity and importance, IT leaders are entering a new era of data management. There is increasing demand to make data freely accessible, understandable, and actionable across business units, departments, and geographies to enable digital transformation efforts. At the same time, many global companies are under pressure to comply with varying country-specific rules about what data may be shared within or beyond geographic borders.
The good news is that CIOs can take advantage of new data management techniques and tools to strike the right balance between accessibility and control. Now is an opportune time for IT leaders, working in partnership with their business peers, to develop an “enterprise data sovereignty” road map to facilitate understanding of data relationships, guide data storage, and manage data rights. And by employing new cognitive capabilities, they can automate aspects of data management, redesign data architecture, and elevate data stewardship.
A holistic approach to data architecture and management can help improve the performance of this business-critical asset, helping to foster innovation and growth. It can also serve as a platform for helping organizations comply with existing and expected national data sovereignty rules around the world.
Data Wants to Be Free
There is no question that the ability to strategically manage ever-growing stores of data will be a competitive advantage in the digital age. In many companies, data collection, access, and management remain siloed by department, business unit, or geography. However, as companies seek to digitally transform, data must be more freely accessible throughout organizations for companies to realize their full potential.
Historically, few companies have been able to master data management—even when much of that data was structured and stored in tables or basic systems. As data has grown in volume and variety, those challenges have multiplied. With many organizations doubling their data every two years, short-term strategies for data computing and storage can quickly become obsolete. New data management architectures and strategies are likely needed to accommodate the big data explosion.
That’s where enterprise data sovereignty comes in: It’s a way for IT and business leaders to develop a holistic data management strategy for the organization, with the goal of making data available, consistent, and controlled throughout the company. CIOs who take this approach know where data is stored; who has access to it; and how or whether it moves beyond business unit, geographic, or company boundaries.
Over the next 18 to 24 months, more companies will likely begin modernizing their data management in this way, working to increase data discipline and availability. Viewing data through the lens of enterprise data sovereignty can help companies solve challenges related to architecture, global regulatory compliance, and data ownership.
Whose Data Is It Anyway?
One of the first issues IT and business leaders confront in developing an enterprise data sovereignty plan is data ownership. In the past, IT owned the systems and, therefore, the data. That’s not necessarily the case anymore.
Going forward, the question of data ownership will be answered differently in different companies. There will be no one-size-fits-all approach. Many organizations will employ a data steward focused primarily on data quality and uniformity. Some organizations are hiring chief data officers, but their focus is less on managing data than on illuminating and curating the insights the data yields. In many companies, there may be no de facto owner at all. In any case, the most important decisions may concern not who owns the data, but rather what principles govern data management and access and how those rules are operationalized.
Organizations that are beginning to master enterprise data sovereignty share some common success factors. First, they bring together key stakeholders to determine goals for data quality, uniformity, collection, storage, and aggregation. They also have a data management function, owned and led by the business, that enforces decisions about management, governance, and consumption. This hybrid approach—having some level of centralization to enforce decisions made by a cross-functional stakeholder group—is typically the most effective way to operationalize enterprise data sovereignty.
Data Architectures for the Future
Creating a modern data architecture is challenging for most organizations. Even for those with a track record of success, traditional master data management, data quality, and data governance processes may fail to keep pace with data flowing in from new places in different formats.
IT leaders who want to build a platform for enterprise data sovereignty consider not only how and where data is stored, but also the sourcing and provisioning of authoritative data, metadata management, master data management, information access and delivery, data security, and data-archiving capabilities.
Thankfully, today’s IT leaders can take advantage of advanced components to build their data management architectures. The following new cognitive capabilities can help organizations better manage data across its life cycle—from consumption to analysis:
- Ingestion and signal-processing hubs can make sense of structured and unstructured data from public, social, private, and device sources.
- Cognitive data stewards can help users understand new compliance requirements and augment human data stewards.
- Data integrity and compliance engines work to enhance data quality and fill data gaps to help ensure data quality and integrity.
- Dynamic data fabrics understand the interconnectivity of data and can maintain metadata and linkages as data moves through different systems.
- Enterprise intelligent layers employ machine learning to illuminate deep data insights and help increase confidence in real-time analytics.
Maintaining Global Compliance
National data sovereignty rules, such as the much-anticipated General Data Protection Regulation in the European Union, are also an issue. While the cost of compliance with various regulatory requirements will be substantial, the price of noncompliance is likely to be even higher.
Taking an enterprise data sovereignty approach can help companies deal with the thorny issue of maintaining compliance with regulatory and privacy requirements that differ dramatically by nation. CIOs can also deploy technology solutions for global regulatory compliance. A sophisticated rules engine deployed directly into cloud servers can apply myriad rules to data dynamically to determine which stakeholders in specific jurisdictions are allowed access to what data. IT leaders can also segregate data into logical cloud instances by legal jurisdiction and deploy controls to limit cloud access to those data stores to users in each locale.
At a business level, it can also be valuable to shift the focus from managing and sharing data to managing and sharing insights. Insights, after all, can be transferred freely throughout a global organization even when data cannot.
Where to Begin
The Holy Grail for IT leaders is an enterprise data sovereignty strategy that can handle growing volumes of data in an agile, efficient, and controlled manner. The distance between today’s data management reality and that end state can seem daunting, but there are some actions IT leaders can take to move in the right direction:
- Pay down data debt. Smart IT leaders can confront the extent of their existing data sprawl in order to understand the magnitude of the issues to be addressed.
- Begin at the beginning. Many of a company’s data problems can be traced upstream to the information supply chain, where CIOs can focus their efforts to link, merge, route, and cleanse data.
- Use metadata—and lots of it. Adding metadata to raw data at the point of ingestion is among the best ways to enhance data context.
- Employ a cognitive data steward. Leveraging advanced AI technologies to assist human data stewards can free data professionals to focus on the bigger data sovereignty picture.
The enterprise data landscape is only becoming more complex, with new and increasingly unstructured data coming online every day and a dynamic global regulatory environment. That’s why forward-looking IT leaders are beginning their data modernizations efforts today.
—by Bill Briggs, principal and chief technology officer; Juan Tello, principal; and Ashish Verma, managing director, Deloitte Consulting LLP