“…we are focused on making what was once impossible–possible”
EM: Tell me about your background and how you got to where you are today.
Bill Sullivan: My background is somewhat unique in the federal space. I came from the state, local and education (SLED) market, running a series of North American SLED organizations starting at IBM/Tivoli, and spending years at PeopleSoft (before acquisition) and Oracle (after) running North American SLED for applications. Four years before joining Cloudera I led the public sector at Informatica. While there are many differences in working SLED versus federal the similarities come in the network of relationships required within the broader technology community for transfer of large applications. Regardless all areas of the public-sector face similar challenges in modernizing legacy technology, while trying to embrace machine learning and analytics to better serve constituents. I’ve been here at Cloudera for almost two years now and in my entire career to date I have never seen such truly ground breaking technology.
EM: How would you talk about the solutions and services that Cloudera focuses on?
Bill Sullivan: Cloudera is focused on solving the world’s greatest challenges through machine learning and analytics. We deliver value for customers in three primary areas: protecting your business, connecting products and services through the Internet of Things (IoT) and understanding your customers or constituents.
- Protecting the customer’s organization: We look at it from a data security perspective. The most important aspect to consider is giving organizations complete enterprise visibility. We also work with customers to optimize their SIEM systems. By offloading much of their data into Cloudera, agencies can improve analytic flexibility by deploying existing machine learning and BI tools on Cloudera. This enables advanced threat detection and response, helping our customers thwart cyber-attacks. Equally as important to government agencies is fraud detection, which costs government organizations like CMS billions each year. Being able to cost effectively store and analyze vast amounts of data allows organizations to identify patterns of deceit and stop bad actors from abusing government resources.
- Connected products and services–the ‘Internet of Things’: Within the public sector we are working with a lot of customers to help them manage the immense volume, velocity and variety of data that is being generated from social media, from sensor data, from wearable devices. We help our customers use streaming data to manage everything from anticipating maintenance needs for vehicles to tracking road safety during inclement weather.
- Understanding the needs of customers: Using a modern platform for machine learning and analytics, optimized for the cloud like Cloudera, can help public sector customers engage with their constituents and better understand the programs and services that people are using and then track their success. This has a different flavor in the public sector than it does for a commercial entity. For example, in education we are working with several colleges and universities to track student success of distance learners to ensure that they remain engaged in a course of study. Analytics helps institutions identify patterns of distress for students who might need intervention and then gives them an opportunity to course correct and support a successful outcome.
EM: How is the federal government embracing the Internet of Things? Where do you see applications in the federal government?
Bill Sullivan: The largest we can discuss is within the logistics arena and in the healthcare space–the DoD logistics and global supply chain. In healthcare, we see a lot of potential cost savings for the HHS and CMS. We also work with agencies like the Department of Homeland Security to rapidly ingest videos and images at scale to enhance public safety by tracking criminals, terrorists and to better patrol our borders. This is also useful for state and local law enforcement given the increasing demand for body cameras to review officer response or for use in patrol cars to capture license plates and cross-reference with arrest warrants in real time. The fact we are able to ingest and aggregate large quantities of video and sensor data–on premise or in the cloud–advances the mission of both anti-terrorism and law enforcement. Predictive maintenance is another area where we have had significant success in the private sector with great applicability across government. The federal government has very similar needs, and being able to manage and maintain assets more efficiently through sensors has the power to transform the way the government agencies oversee vehicles and buildings, how they monitor and optimize everything from power consumption and even track warfighters’ vital signs during deployment. At Cloudera we are focused on making what was once impossible, now possible, and the excitement continues to grow.
EM: Can you briefly talk about Cloudera’s role in healthcare?
Bill Sullivan: When you study the aggregation of healthcare data, it demonstrates the potential to fundamentally change the way we deliver patient care – starting with a deeper understanding of genomics. We have the opportunity to fundamentally change and tailor how healthcare is delivered to a speciﬁc individual, given their genetic makeup. This means that you have much more precise treatment plans, less experimentation and lower costs with improved success rates. It costs less to deliver medicine to a particular person because you better understand how they are going to respond to varied treatment modalities, and overall you can spend less on healthcare. Healthcare is currently going through a transformation because of data analytics used to examine how much money is spent. Where it is spent as a result of a diagnosis? What are the long- term implications for catching chronic diseases earlier on the patient’s lifetime? Instead of waiting until someone is 60, and having a million-dollar cardiac event in an emergency room, they might be able to catch a growing problem when the patient is 40, and be able to manage it over time, improving the patient’s life and requiring far fewer resources on behalf of the healthcare industry. This is an example of harnessing data to offer predictive analytics around patient care, and is going to fundamentally change the way we deliver healthcare. We are improving people’s lives by doing it, and that is deeply rewarding.