With Dataworks Summit kicking off in Washington, DC next week, we are super excited to have Charles Boicey MS, RN-BC and Chief Innovation Officer for Clearsense, as one of the keynote speakers. A notable expert and clinical information systems specialist, Charles, offers his 25-plus years of strategic leadership. He is a successful architect of healthcare data warehouses, clinical and business intelligence tools, big data ecosystems, and a health information exchange.
The Enterprise Data Cloud – A Healthcare Perspective
Healthcare organizations have made significant investments in implementing systems which yield an abundance of data. This data is often siloed and not integrated across systems or workflows, so the data is static, latent, and incomplete, reducing the value of the information. What’s needed most is the ability to ingest, organize, and translate all this data in one place, in real-time and in proper form. Join Charles Boicey, @ClearsenseLLC, as he tells the story of how Clearsense is applying Data Cloud technologies to healthcare. He will cite use cases and outcomes around: affordability for all healthcare organizations, completeness of serving clinical, operation, financial and research needs, as well as making it future proof.
Clearsense is a technology company based in Jacksonville, Florida providing organization stakeholders with the ability to unlock the power of their disparate data sources to lower costs, increase revenue opportunities, and improve outcomes. The Clearsense Platform solves the fundamental data problem by ingesting, organizing, and translating all healthcare stakeholder data into one place, in real-time, and in proper form in any combination for any internal or third-party analytics functions.
Join us at DataWorks Summit to see this great talk along with many other sessions by companies in the big data community. Check out this list below to see some of them in action:
Comcast
Barbara Eckman from Comcast is another keynote speaker, and is also presenting a breakout session about Comcast’s streaming data platform. The platform comprises ingest, transformation, and storage services in the public cloud, and on-prem RDBMS’s, EDW’s, and a large, ungoverned legacy data lake.
PayPal
PayPal will give a breakout presentation covering its journey into real-time analytics, including how the company is processing and handling real-time data at scale using Apache Kafka, Spark streaming, and Akka streaming. Some use cases require data to be available in near real-time, to make timely decisions and improve the customer experience. The analytics and data platform is powering different data needs, use cases, and growth.
American Water
American Water will share how bringing IoT to fleet management can provide value to the customer. In the utilities industry, fleet management plays a major part in the business. The front line is one of the largest parts of the business whether it is the field employees working on mains, or those working on the customers’ property. American Water leverages NiFi to track metrics against a simulated truck, showing the initial values in capturing this type of data.
Walmart
Walmart will be sharing about how its construction of a Finance stream in its data lake helped reduce and eliminate efforts on data mining and cleansing. This enabled the team to focus on data analytics and making insightful, well-informed, and collaborative decisions. Additionally, building processing pipelines to consolidate data from its source systems like store registers and e-commerce order databases helped to create centrally-managed, well understood, consistent, reliable, and secure data sets that can be accessed by users across Walmart via diverse tools from Hive to Tableau customized for use cases.
Walgreens
Walgreens will be sharing about its cloud automation journey. The company currently has Hadoop clusters deployed in both on-prem and cloud. There were demands for speedy delivery of new Hadoop environments. In order to meet the business needs, Walgreens has used automation processes to build and maintain Hadoop clusters. Using automation, the team has significantly reduced the build and delivery times for new Hadoop environments in Azure.
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