In Part 2 of this 2-part blog series, we examine the technologies that are driving the changes in the world of data analytics and what the future holds.
Technologies Empowering Data Analytics Today
In our previous blog (Healthcare Analytics Matters: A Unique Data Analytics Approach) we discussed the importance of data analytics, and how it can empower and positively impact businesses with insightful information. Its relevance in today’s ‘big-data’ environment comes into sharp focus when you consider the exponential increase in the enormous quantities and speeds of incoming data.
As a result, statistical data analytics is continuously evolving, using even more complex and advanced technologies, making it possible to gain data insights that are more accurate and detailed.
It won’t come as a surprise to know that some of the data analytics technologies used includes machine learning, data mining and predictive analysis.
Depending on the organizational culture or challenges, when a data analytics solution is embedded into the data management platform, whether it is a DIY solution or an out-of-the-box solution (for example, Amazon QuickSight), the transformational journey towards a ‘data-driven’ environment can be achieved.
The healthcare industry has unique challenges when it comes to big data analytics: data security, HIPAA data compliance, integration of multiple systems (EPR, HIS, etc.), numerous data sources, to name but a few. In addition to that, data may come in the form of imagery (x-ray or scan images), and for that reason healthcare analytics needs to provide the most human-like intelligent features.
Working in partnership with Amazon Web Services, SourceFuse is continuously developing and leveraging the very latest in machine learning (ML) and artificial intelligence (AI) technology, transforming modern business analytics:
- Predictive Analytics: Leveraging ML algorithms (AWS SageMaker) to go beyond basic insights derived from historical data, and to forecast or predict future outcomes (Amazon Forecast). Particularly within healthcare, it is possible to automate image or video analysis specific to requirements (Amazon Rekognition)
- Descriptive Analytics: Examining data and representing the results visually (for example pie charts, tables, charts, etc.) to identify patterns or trends; adopting natural language processing (Amazon Comprehend) enables relationships in text to be analyzed where it may be more unstructured (for example within emails, healthcare provider notes, etc.) or through speech recognition in audio recordings (Amazon Transcribe)
- Diagnostic Analytics: While descriptive and predictive analytics answer the question “what happened?”, diagnostic analytics helps to answer the question “why did it happen?”. This requires a deeper-dive into the available data, or ‘data-mining’, finding answers to mission-critical questions, leading to more valuable decisions.
Learn more about SourceFuse’s approach to Modern Data Analytics.
Where is the Future Headed?
As evidenced, ‘big data’ has already driven the need for accurate, sophisticated, state-of-the-art business intelligence solutions. But where is the future headed, is the real question?
Gartner’s 100 Data and Analytics Predictions Through 2024 latest annual predictions confirms that data analytics is an increasingly critical part of any private or public sector organization, and planning for future developments is key to their strategic success. Some of Gartner’s overall predictions include that by 2023-4:
- 30% of senior business leaders will rely on automated data analytics to drive business-related decisions, compared to only 3% today
- The ML engineer will be the fastest growing role in the AI/ML space
- 85% of AI solution vendors will focus on open architecture
- Customers will use blockchain licenses to secure 30% of their sensitive data
- Almost all legacy applications migrated to the cloud will require optimization to become more cost-effective
- 30% of CIO’s performance will be measured on creating value for the business
For the healthcare industry, Gartner states: “Healthcare disruptors are leveraging cross-industry partnerships and emerging technologies to create new digital business and operating models that color a compelling health landscape”.
AI/ML, NLP and cloud technologies are already transforming the way healthcare organizations provide patient satisfaction and better outcomes, and Gartner predicts:
- By 2022, the general public will have a core smartphone app for PHI (personal health information), and that 75% of healthcare providers will contribute EHR data
- By 2023, 25% of the top 50 life science companies will be using IoT sensors and devices to enhance existing clinical product monitoring, tracking and management technologies
- By 2024, 50% of healthcare providers will integrate digital monitoring and diagnostics into clinical workflows
- By 2025, AI and advanced technologies will be the norm for US healthcare insurance companies
Prescriptive analytics is also set to be commonplace in the future, drawing on both descriptive and predictive analytics to provide even more powerful business intelligence.
Prescriptive analytics enables organizations to ask the question “what should we do?”, that then delivers a number of suggested or recommended strategies for improvements. While this is still a relatively new and complex field, having the ability to predict outcomes based on different courses of action will have a huge impact on how businesses make their decisions and mitigate risks in future.
The future of data analytics is exciting! It continues to evolve and advance, automatically unlocking the powerful stories that our data can teach us, and empowering business decisions.
Take your next steps towards a data-driven future and talk to our experts today about Data and Analytics Services at SourceFuse.
