Big Data Ecosystems
Healthcare CIOs are besieged with a veritable data tsunami.
With data volumes doubling every 18 months, looking the other way is no longer an option. But savvy leaders in healthcare are not only facing the sizeable challenges presented by big data head-on, they’re also recognizing them as uniquely powerful opportunities to improve clinical outcomes, deliver better and more personalized experiences and reduce the inefficiencies and exorbitant costs that plague the industry.
Big data represents a way for healthcare to move beyond reactive disease treatment to the proactive support of wellness management. Achieving that transformation requires fundamental changes to the traditional approach to data management in healthcare:
- A scalable, modernized data architecture
- Readiness for real-time responsiveness
- A deep and lasting connection to business value and leadership
Gaining a Big Data Advantage
In healthcare, big data isn’t just about the increasing number of data elements being captured through electronic medical records, medical devices or care management systems. The big data opportunity for healthcare providers and payors impacts every step of your information value chain from origination to enrichment and integration to decision-making.
Supercharge Your Information Value Chain
It used to be that getting value from data was seen as a simple matter of extracting source data from operational systems, transforming and integrating it in an enterprise data warehouse, building dimensional structures for slicing and dicing, and delivering self-service reports that decision-makers could run anytime they needed. The big data value chain is similar at only the highest-level concepts. Implementing the same traditional architecture with a big data ecosystem won’t cut it.
Modern big data ecosystems are built from the ground up with the assumption that your solution will need to scale to support a growing volume and variety of data, but your analytical needs will also be growing in complexity and quantity at the same time. The ability for your analytical pipelines and tools to support data scientists who want to employ the latest in deep learning and genetic algorithms will be critical in preventing a chaotic proliferation of overlapping technologies and work efforts.
Adapt to Any New Data
The data tsunami is real and to fully understand the forces that impact our industry, you need to be able to quickly sift through new data sources, identify those that have both high value and high quality, and integrate them into your analytical capabilities. Not only do you need new technologies to bring those data into your data ecosystem, but you need access to experts who are skilled in the nuances of healthcare data domains, techniques for modeling and integrating non-traditional data, and the tools (both commercial and open source) that make it possible to work with those sources in a meaningful way.
New sources of data can make or break a competitive advantage. Imagine if you really understood which primary care physicians were getting the most referrals, through what channels, and why? If that physician can’t take new patients, where should they be referred to produce the best possible relationship or which new primary care physicians should be marketed to what population on Facebook? You can’t do these analyses without better feedback, social media monitoring and population information.
Deliver Value Where it’s Needed, When it’s Needed
The last time that you needed to add a new source of data to your data warehouse, how long did it take? What was your process? Did it involve several weeks of upfront data profiling and analysis to understand and model the data into existing conformed dimensions and new fact tables? What was the time between a business leader identifying the critical need to understand some aspect of business operations and when she could finally make an impactful change?
The ability to see a new way of doing business and being confident in the advantage that change will provide has a powerful impact on the organization’s bottom line and, in some cases, the bottom-line for people’s livelihood and lives. Modern data architectures have to include the ability to source and integrate data from both traditional and new data sources within hours and minutes. Your methodology and relationship with business leaders and decision makers has to be able to accommodate this demand for information.
A Valuable and Trusted Partner
At Amitech, we’re committed to helping our customers understand, design, build and optimize big data ecosystems that help them to capitalize on the opportunities for meaningful and lasting change in the industry.
For some of our customers, that looks like:
- Transforming narrowly defined, static data warehouse solutions into dynamic and scalable analytic platforms using a variety of big data technologies
- Leveraging data lake architectures and tools to integrate structured, unstructured, and other varieties of data within a single big data ecosystem
- Taking advantage of new economic models offered by the elasticity of cloud infrastructure and high-level cloud-native analytical services
- Adopting new data integration (ETL and ELT) tools powered by distributed and real-time data processing platforms
- Implementing big data visualization tools that provide decision makers and analysts an intuitive understanding of the insights behind large amounts of data
- Strategic roadmaps that provide rapid access to new capabilities without the risks of wasting time on unproven technologies or building solutions that will be obsolete upon delivery
If you’re interested in discussing what it could look like for you, let’s talk.
