Over the last 10 years there has been an explosion in data gathering. For example, a study conducted by IDC in 2021 estimated that on average, approximately 270 GB of healthcare and life science data will be created for every person in the world. The National Library of Medicine predicts that by 2025 the world’s human population will be 8 billion people. The scale and scope of having this amount of data to leverage is both enormous and daunting.
This is not a new problem, the phrase “Data Rich, Information Poor” was coined in 1996 to define the struggles healthcare organizations had in reviewing medical data, records, patient information, and medical history.
If this was identified as a problem 25+ years ago, why is it that when we collect so much data today, we become information poor? CIOs, and CDOs are asking the same questions: “How can we harness our data to gain insight into our business and create new and innovative ways to enhance customer experiences?”
Manage Data Correctly With Cloud
It all starts with how you manage and leverage the data you collect. For example, the challenge for healthcare and life science organizations is how best to store the data so it can be analyzed to provide value. It’s also important for that same data to improve patient care and reduce costs. Managing sources of data is another challenge that is growing exponentially, as data coming from new sources that is increasingly diverse needs to be securely accessed and analyzed by any number of applications and people.
This creates the need for scalable, adaptable, and secure cloud infrastructure. It’s a primary driver for organizations to move to the cloud from legacy on-premises systems, and it opens new possibilities based on the pace of innovation from cloud providers. Choosing a provider based on these parameters will help enable the goal of better management and insights derived from the data.
Capitalize on Connectivity and Collaboration
There is a huge shift moving away from traditional data warehouse architecture, and that’s because there are many different silos. Analyzing the data accurately is a huge challenge due to a lack of computing capabilities. The result has many organizations looking to extract more value from their data but struggling to capture, store, and analyze all the data being generated by today’s modern and digital businesses. As companies have accumulated vast amounts of data, that data lives in different silos, making it difficult to analyze. The silos cause multiple problems — the data needed for a given workload may be split across multiple silos and inaccessible, the silo where the data lives might not meet the price performance requirements for a given workload, and the silos may require different management, security, and authorization approaches — increasing operational cost and risk.
Put the Pieces Together to Succeed at Scale
Organizations are looking for a highly scalable, available, secure, and flexible data storage solution that can handle extremely large data sets. To achieve this, companies should build data platforms that can store all the structured and unstructured data, use an open data format, and tag data in a central, searchable catalog. They also need to be able to run multiple analytics services against their data to ensure they have the right tool for the job. For example, healthcare organizations can build state-of-the-art platforms, such as AI-assisted decision support systems that leverage artificial intelligence and existing data to analyze images and symptoms. The resulting analytics can be used to help care providers predict levels of need.
In a world full of unstructured and structured data, there exists a deep trove of valuable information. By moving that data into a solid cloud infrastructure and leveraging advanced data analytics, companies can more effectively mine and gather the information they need — making them both data rich, and information wealthy.