- Big data analytics is becoming more and more prominent in healthcare as organizations are looking to analytics for assistance in population health, precision medicine, and value-based care.
The global big data market is expected to reach $81 billion by 2022, according to Research and Markets. The main driving factor in this growth is attributed to Internet of Things (IoT) and connected devices becoming standard across all industries.
Report authors cite the need for organizations to leverage unstructured data collected by cloud applications, IoT devices, and enterprise operational technology. Authors stated that new big data analytics models are emerging to reduce friction when sorting and analyzing data. As a result, big data-as-a-service (BDaaS) deployments are expected to grow across all industries.
The growth of mobile and IoT devices heavily impacts the unstructured data that requires a big data analytics solution.
Last year, health IT spending nearly doubled its investments in mobile health devices, making it far and away the most invested in health technology of 2016. Mobile device initiatives extend beyond smartphones, laptops, and tablets, to include IoT devices.
Healthcare organizations that store the data collected by mobile and IoT devices can use this data to get the best value out of their time and provide patients with faster and more accurate diagnoses.
Big data solutions are significant to healthcare organizations looking to implement value-based care initiatives. Solutions that offer scalability and visibility are becoming necessary due to value-based care.
Value-based care begins with building a solid health IT infrastructure comprised of tools used to process faster and use less expensive resources. Organizations need to ensure they are using all health IT infrastructure solutions efficiently and effectively so resources are not wasted.
By using cloud computing, BDaaS solutions save organizations the cost of large on-premise deployments that take up space and that are expensive to maintain. Organizations are only obligated to pay a monthly subscription fee, depending on the resources they need, rather than paying the upfront cost of equipment they may or may not need in the future.
Last month, CenturyLink and Cloudrea announced the collaborative release of a big data managed service. The BDaaS solution uses cloud bare metal servers to give organizations more scalable storage and compatible applications.
Many incentives healthcare organizations are adopting rely on a big data analytics solution that can support their unique needs. The CenturyLink and Cloudera solution also provides users with the visibility needed to manage network activity and structure the analytics process.
Cloudera contributes its use of Hadoop, an open-source distributed data storage and analytics application, as a software-defined framework to handle structured and unstructured data by distributing it among different data processing nodes to process batches of data quickly.
"With numerous vendors offering components for big data solutions today, a key to achieving success for customers is services and support. Providers that offer data and analytics consulting, deployment support and customized infrastructure and application solutions, should be able to deliver enhanced strategic value for customers,” 451 Research Senior Analyst of Data Platform and Analytics James Curtis said in a statement.
Cloud based big data solutions offer organizations more support and service because organizations are not charged with running the solution themselves. Entities save money on hiring on-premise experts to manage and maintain every aspect of the big data solution.
Healthcare organizations will continue to adopt connected medical devices and other IoT devices that will collect data in various formats. It is unlikely that every device transmitting information to the data center within an organization will ever have a single format for its unstructured data. A scalable big data analytics solution will provide entities with the resources to make use of collected unstructured data.