2019 Federal Data Strategy: Prioritizing Data as a Strategic Asset

By Toné Mason, Senior Analyst

In June of 2019, an update to the Federal Data Strategy was released including the final Principles and Practices and draft Year-1 Action Plan. The final Year-1 Action Plan is anticipated to be released in September.

Vendors should understand what’s in the plan and make sure they adapt their sales strategies and messaging to address the new plan goals:

  1. Enterprise Data Governance – The federal government needs to have a plan for how to best protect their data. This includes the formation of data policies, data protection strategies and a way to monitor for compliance. Quality and integrity of data will need to be protected and monitored as best as possible.
  2. Access, Use and Augmentation – Ensuring continuous and reliable access to data will be vital. Additionally, it will be key to make the visualization of data as user-friendly as possible and ensure that proper information silos are in place, whether for an application for the public or for soldiers on the ground.
  3. Decision Making & Accountability – There are vast amounts of diverse types of data currently not being utilized. Preparing this data to be consumed can be extremely challenging. Transforming this data into actionable, real-time intelligence to inform decision making is the end goal and is even more challenging.
  4. Commercialization, Innovation and Public Use – Making federal data assets available to external stakeholders in an easy-to-use format is a key priority. This will facilitate the creation of new applications where advanced technologies and visualization techniques can be applied to transform the data into useful, consumable information for a wide range of use cases.

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Smart Cities to Watch Part 2: Denver and Richmond

By Rachel Eckert, SLED Manager

In my last blog post, I looked at smart cities initiatives in Boston and Atlanta. This time, we’ll take a look at what’s happening in two more forward-thinking cities: Denver and Richmond.

Before we do that, however, it’s worthwhile to revisit the three things you’ll need to keep in mind as you build an ongoing relationship with decision-makers in those cities:

Align your solutions to each city’s goals. To become a long-term service provider in the smart cities landscape, you need to show that your technology can help provide better, more efficient services.

Tie your technology to the delivery of citizen services. Technology doesn’t exist in a vacuum. Make sure that you can explain how your technology can improve services to citizens and the value it brings to the city.

Strategic partnerships are key. Smart cities need to technologies to integrate with other platforms and applications. Partnering with vendors that provide complementary applications and platforms will offer an integrated solution that city decision-makers will find compelling. Read more of this post

Data Centricity: The Heart of Federal IT

Tom O'Keefe

By Tom O’Keefe, Consultant

If there’s been a common theme I’ve been hearing lately, it’s data centricity.

It’s a fundamental shift in federal IT that’s been building for a few years that could have broad implications for the types of technology investments agencies will look to make in the future. Federal agencies are beginning to realize that not only is data their core asset, they know they need to make start making investments in the stewardship and utilization of that data. It’s not enough to just have data or protect data, that data needs to be operationalized and transformed from data to knowledge to action – and support the execution of the mission.

At an AFCEA Bethesda breakfast I attended in March, speakers from the Departments of Defense and Homeland Security affirmed the increasing understanding within their agency of the value of the data they capture throughout the course of their operations. It’s fair to note here that agencies have been talking about making better use of their data for years, but much like we’ve seen the slow and steady progression to cloud adoption, I believe we’re seeing a steady progression toward realizing the importance of data and turning it into actionable intelligence to enable the mission. Read more of this post

AI and Analytics: Must Haves for Our Naval Force

Lloyd McCoy Jr.

By Lloyd McCoy, Marketing Intelligence Manager

There’s a real sense of urgency in the Navy.

Increasingly, at conferences (most recently at AFCEA West) and in sidebar conversations, I hear maritime leaders talk about “Great Power Competition” and how we’ve reached an inflection point in terms of how dispersed our fleet can reasonably be while maintaining effectiveness with current capabilities.

The mantra “do more with less” has been around since time immemorial but there’s a widespread belief that while the U.S. military will always have the advantage in air, land and sea, artificial intelligence (AI) looks to be an equalizer. There’s also the belief that we are only at the beginning of the adoption and development cycle for AI.

How do you fight a war against an adversary that can predict what you are going to do before you even know? Ladies and gentlemen, we are in an AI arms race. Read more of this post

How NASA is Dealing With Their REALLY BIG Data

Tom O'KeefeBy Tom O’Keefe, consultant

Big Data and artificial intelligence are top of mind at NASA this summer. The agency has always collected, sorted, and stored a massive amount of data and made that data available to the public. Now, it’s looking to leverage big data tools to better understand more of the huge volumes of information it has at its fingertips

The focus is on increasing efficiency wherever possible, and it’s this approach you should keep in mind when you’re talking to NASA this year. Here’s what NASA is going to be working on, so make sure you’re tailoring your message appropriately:

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3 ways government is investing in big data

Stephanie Melonibig data, governmentBy Stephanie Meloni, consultant

Big data is shaping up to be one of the bigger areas of IT growth within government. The federal market is expected to grow to $9 billion in 2018 and continue growing at an annual rate of 10 percent for the next several years.

Several factors are driving the growth, including the government’s increased attention to its data. The amount it collects and analyzes will only increase with more devices, sensors and upgrades of legacy enterprise systems. Internet of Things (IoT) will be a key driver for agencies that want to revolutionize their data and analytics practices.

The government will also be looking at data management and analytics solutions to improve operations, finance, human resources and healthcare challenges. Data analytics is vital to all government agencies, as analytics can help respond to cyber challenges and save money—two hot buttons for all government customers.

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What you should know about the future of machines

machine learning, artificial intelligenceBy Mark Wisinger, senior analyst

2017 saw machine learning become the de-facto in-vogue technology, whether the conversation was about data, cybersecurity or even traditional business systems.

In December, Google’s AlphaZero chess engine, utilizing Google’s DeepMind AI, crushed the incumbent chess engine champion, Stockfish. Google’s DeepMind relies heavily on machine learning – the AlphaZero chess engine did not start with any human knowledge, yet was able to learn how to beat Stockfish in 400 hours through machine learning. It’s a clear victory for machine learning – but one that’s easy to simulate. This is a much easier use case than identifying noise from cyber threats or prioritizing and cleaning multiple forms of data.

At immixGroup’s Government IT Sales Summit, we hosted a discussion on artificial intelligence (AI) and machine learning with Ron Gula, president and co-founder of Gula Tech Adventures and former CEO and co-founder of Tenable Networks, Dr. William Vanderlinde, chief scientist at the Intelligence Advanced Research Projects Activity (IARPA) and Rich Friedrich, senior director of cyber security analytics at Micro Focus Government Solutions.

Here are key takeaways to keep in mind when you discuss machine learning and AI with your government customers:

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