Public sector organizations generate huge volumes of log data each day from servers, virtualization infrastructure, databases, security systems, applications, and more. And, according to IDC, unstructured data is growing at an annual compound rate of 60%. But due to its unstructured nature, that data, often called machine data, is much harder to analyze than structured data.

Technological innovations in the storage and computing capacity in the world of data has moved exponentially – especially in the healthcare space.  One of the most dramatic use cases is in the field of genomics.  As Andrea Norris, the CIO for NIH mentioned at a public sector Healthcare Summit on IT Modernization last week, technology has greatly increased the speed and lowered the costs associated with gene sequencing.  Originally, when the human genome project completed the task, it took around 13 years with funding around 2.1 billion dollars (the project was from 1990–2003)

Expert Panel: The Challenges and Opportunities for Modernizing Data Protection

As online data has become ubiquitous, managing that data has become as important an endeavor as amassing and storing it. A host of issues surround data management, not the least of which is security. But many others loom as data increases exponentially both in size and in importance.

The state of our nation’s infrastructure is grim. The most recent report card from the American Society of Civil Engineers (ASCE) gave U.S. infrastructure an overall score of “D” for “poor” or “at risk”.

This time of year brings reflection and blessings to count. The Big Data, Analytics and Data Science team at DLT has a lot to be grateful for, as we’ve grown and expanded at an accelerated pace, finding success along the way. As the team and portfolio grow, so do the strategic partnerships, initiatives, activities, and tactics.

Law enforcement and intelligence agencies deal with large volumes of disparate data on a daily basis. Analyzing all this data across multiple data silos and structures, each with their own levels of security permissions, is a big challenge.

The Federal Data Strategy principles (https://strategy.data.gov/principles), as currently articulated, are a set of best practices and guidelines, which could be utilized to govern the development and maturity of an organization’s management of data as an asset.  However, without guidance or a framework within which to actualize these principles, these principles may well be rendered a wish-list.

Form follows function – and so should your organization’s data!

Digital twins may sound like the stuff of science fiction. Yet, digital twin technology is one of the top 10 strategic technology trends for 2018, according to research firm Gartner, Inc. Gartner® recently announced 48% of surveyed organizations working with the Internet of Things (IoT) say they are already using, or plan to use, digital twins in 2018. Gartner’s survey also indicated that adoption of digital twin technology is expected to triple by 2022.

There are many opportunities in the public sector for data science and data analytics, yet, almost as many challenges. When we kicked off Big Data Month at DLT, we asked our Chief Data Scientist, Sherry Bennett, for her insights. What became clear is that the obstacles to big data success are universal to both the public and private sector: “…everybody…is grappling with the same thing.