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Data Management and Analytics

By Jonathan Alboum posted May 14,2019 02:36 PM


By Jonathan Alboum, Chief Technology Officer, Public Sector, Veritas Technologies

Data Management and Analytics is #8 on NASCIO’s Top 10 State CIO Priorities for 2019. Considering that we create more data today than ever before, this isn’t surprising.

Most state CIOs struggle to gain visibility and insight into their data, specifically unstructured data. This type of data — emails, documents and image files — expose organizations to increased risk, security vulnerabilities, and PII leaks. This problem is intensifying. Our data grows at a rate of 49% year-over-year and 80% is unstructured.

Unfortunately, most of the data in our organizations is “dark data”, meaning that we store it, but do not know what it is. Sometimes we know what it is, but it’s redundant, obsolete, or trivial (ROT) data. Studies show that state agencies operate on only about 15% stored data.

Our lack of data insight hinders opportunities to embrace analytics, evidence based decision-making, and AI/ML opportunities. It also opens us up to significant monetary penalties for failing to comply with sunshine laws and emerging requirements, like California’s new privacy law.

Today’s hybrid, multi-cloud world, exacerbates the challenge of data visibility. Studies show that state CIOs don’t possess tools to manage data effectively, impacting their ability to search, discover and review data. This is a critical failing because organizations must be able to locate PII within a very short time to be compliant with privacy mandates, or face significant fines.

There are no simple solutions. However, a good starting point is development of an Enterprise Data Governance strategy.

Data classification technologies are an important enabler of data governance. However, several actions are more important. Based on my real-world experiences across government and industry, I offer the following data governance best practices.

  • Executive sponsorship is crucial. Securing a champion in senior management is key to a successful data governance program. Ideally, the sponsoring executive empowers the Chief Data Officer to work across the organization.
  • Creating a data governance committee is essential. This group is a multi-disciplined team from across the organization. They review risks, evaluate compliance issues, and determine how best to retain data. Data governance is a team sport.
  • Using an Enterprise Data Governance framework or maturity model is helpful in assessing and guiding the program. Various models exist, but an organization should customize a framework for its own purposes.
  • Defensible deletion of data that no longer has value is critical. Eliminating data debris regularly and consistently is a best practice. With a smaller information footprint, state CIOs can reduce risk, more easily find what they need, and use data to create business value.
  • Enterprise Data Governance is an ongoing program, not a project. It is an ongoing effort. Regular reviews must be conducted to ensure the program is followed, and adjustments made based on the findings. The effort never ends.

A state that doesn’t manage its data is limited to transform digitally. Investing in data governance technologies and processes is an excellent first step for any state CIO to take in order to deliver the digital government our citizens deserve.