This document discusses improving practitioner decision making through data and analytics at Auckland District Health Board (ADHB). It outlines Ali Khan's role as Data & Analytics Director and responsibilities at ADHB. It then discusses how ADHB is starting to use previously inaccessible data by applying new technologies to gain better clinical and operational insights. Finally, it proposes a self-service analytics model to enable business users to safely access and use their data to build new insights and drive innovation.
-The Complexities, Challenges and Opportunities of New Zealand’s Health System.
- The Role of Care Coordination.
- DXC Health in New Zealand.
- DXC’s Care Coordination.
- Health Data Analytics.
- Interactive Session.
Presented by:
- Karen Blake, Regional Manager Health Information, Blake Consulting.
- Simon Kingston, Country Manager NZ, DXC Eclipse.
- Antony Zigliani, Practice Manager - BI/Analytics, DXC Eclipse.
Leverage Customer Data to Deliver a Personalized Digital ExperiencePerficient, Inc.
Extreme volumes of consumer data such as interests, behavioral patterns, and purchases are created each day across a variety of applications and devices. Companies must analyze these patterns and interactions to create a total view of their customer that incorporates more than simple demographics. This complete picture of the customer enables companies to provide personalized consumer experiences, meet the increasing demands of the marketplace, and ultimately prevent customer attrition.
Creating a personalized customer experience involves intuitive integration of all available data sources, prescribing the proper action through analytics and automatically tailoring the action through high-speed complex event processing. Many refer to this process as creating a 360-degree view of the customer, and achieving it requires a unified and comprehensive information governance strategy. Architecture, process, and skill sets must be aligned to achieve the responsiveness and accuracy that is required to meet customer expectations.
Our webinar covered:
-How to address the demands of the “Me” generation
-Pragmatic solutions and architecture approaches to the challenges of Big Data in motion and at rest
-The role of Big Data, analytics, events processing, and information management in personalized consumer interactions
-When, where, and how to process Big Data, and the issues surrounding the nebulous digital space
Population Health Colloquium 2015: Mini Summit IV: Who is Your Champion of Cl...Perficient, Inc.
Oracle and Perficient presented at the 2015 Population Health Colloquium.
In this presentation thought leaders explored four types of change (Evolutionary, Disruptive, Imposed and Deliberate) and how all are needed in Healthcare. The discussion covered challenges and goals of integrating analytics (including retrospective data) into the clinician workflow within the EMR and how the Chief Informatics Officer is the best organizational role to champion analytics.
IBM Watson Content Analytics: Discover Hidden Value in Your Unstructured DataPerficient, Inc.
Healthcare organizations create a massive amount of digital data. Some is stored in structured fields within electronic medical records (EMR), claims or financial systems and is readily accessible with traditional analytics. Other information, such as physician notes, patient surveys, call center recordings and diagnosis reports is often saved in a free-form text format and is rarely used for analytics. In fact, experts suggest that up to 80% of enterprise data exists in this unstructured format, which means a majority of critical data isn’t being considered or analyzed!
Our webinar demonstrated how to extract insights from unstructured data to increase the accuracy of healthcare decisions with IBM Watson Content Analytics. Leveraging years of experience from hundreds of physicians, IBM has developed tools and healthcare accelerators that allow you to quickly gain insights from this “new” data source and correlate it with the structured data to provide a more complete picture.
-The Complexities, Challenges and Opportunities of New Zealand’s Health System.
- The Role of Care Coordination.
- DXC Health in New Zealand.
- DXC’s Care Coordination.
- Health Data Analytics.
- Interactive Session.
Presented by:
- Karen Blake, Regional Manager Health Information, Blake Consulting.
- Simon Kingston, Country Manager NZ, DXC Eclipse.
- Antony Zigliani, Practice Manager - BI/Analytics, DXC Eclipse.
Leverage Customer Data to Deliver a Personalized Digital ExperiencePerficient, Inc.
Extreme volumes of consumer data such as interests, behavioral patterns, and purchases are created each day across a variety of applications and devices. Companies must analyze these patterns and interactions to create a total view of their customer that incorporates more than simple demographics. This complete picture of the customer enables companies to provide personalized consumer experiences, meet the increasing demands of the marketplace, and ultimately prevent customer attrition.
Creating a personalized customer experience involves intuitive integration of all available data sources, prescribing the proper action through analytics and automatically tailoring the action through high-speed complex event processing. Many refer to this process as creating a 360-degree view of the customer, and achieving it requires a unified and comprehensive information governance strategy. Architecture, process, and skill sets must be aligned to achieve the responsiveness and accuracy that is required to meet customer expectations.
Our webinar covered:
-How to address the demands of the “Me” generation
-Pragmatic solutions and architecture approaches to the challenges of Big Data in motion and at rest
-The role of Big Data, analytics, events processing, and information management in personalized consumer interactions
-When, where, and how to process Big Data, and the issues surrounding the nebulous digital space
Population Health Colloquium 2015: Mini Summit IV: Who is Your Champion of Cl...Perficient, Inc.
Oracle and Perficient presented at the 2015 Population Health Colloquium.
In this presentation thought leaders explored four types of change (Evolutionary, Disruptive, Imposed and Deliberate) and how all are needed in Healthcare. The discussion covered challenges and goals of integrating analytics (including retrospective data) into the clinician workflow within the EMR and how the Chief Informatics Officer is the best organizational role to champion analytics.
IBM Watson Content Analytics: Discover Hidden Value in Your Unstructured DataPerficient, Inc.
Healthcare organizations create a massive amount of digital data. Some is stored in structured fields within electronic medical records (EMR), claims or financial systems and is readily accessible with traditional analytics. Other information, such as physician notes, patient surveys, call center recordings and diagnosis reports is often saved in a free-form text format and is rarely used for analytics. In fact, experts suggest that up to 80% of enterprise data exists in this unstructured format, which means a majority of critical data isn’t being considered or analyzed!
Our webinar demonstrated how to extract insights from unstructured data to increase the accuracy of healthcare decisions with IBM Watson Content Analytics. Leveraging years of experience from hundreds of physicians, IBM has developed tools and healthcare accelerators that allow you to quickly gain insights from this “new” data source and correlate it with the structured data to provide a more complete picture.
Bundled Payment Changes: Learn What’s New and How to SucceedHealth Catalyst
In January, CMS announced the Bundled Payment for Care Improvement Advanced “BPCI Advanced” program, initiating renewed interest in a total cost of care payment model for specific episodes of care. Regardless of your organization’s current decision to participate, it’s important to understand how bundled payment programs have the ability to significantly decrease your internal costs, broaden your revenue opportunities, and improve patient outcomes across specific populations. The Center for Medicare and Medicaid Innovation’s newest iteration of bundled payments provides another tightly-defined program that allows organizations to scale Population Health Management. Best practice suggests that tactical interventions to assess clinical variation, implement strategic care redesign programs, and to adjust care management-facilitated patient stratification models are important to be successful with bundled payments – so knowing how to implement them is crucial. One organization’s savings is another’s income and without making overhead allocation changes, bundled payments may reduce revenue that has been critically important to maintain hospital profitability. Join this webinar to learn:
* What is new with bundled payments.
* The ramifications bundles can have across organizations.
* Leveraging data and strategic analysis to identify opportunities for bundled payment success.
* Operationalizing successful care program tactics to be successful in bundled payment contracts.
Executive BI, Analytics, Modeling and Insights Strategy Framework PracticesInsightSlides
This presentation looks at the frameworks Executives need to consider in their BI, Analytics, Modeling, and Insights Strategies.
This include frameworks on BI, Analytics. Insights and Modeling strategy creation, strategy development, capabilities, considerations, proven strategy practices, operating models and opportunities.
The Analytics COE positioning your business analytics program for successKiran Garimella
You should consider the following three aspects of your Business Analytics Program:
* The Business (not just data science, big data, and technology)
* Analytics as the DNA of the company (and not just a competency of an elite few)
* A Programmatic approach that sustainable for the life of the company (and not just a one-time project or initiative)
What role do classical statistics, Bayesian statistics, judgment under uncertainty, heuristics, biases, categorical data analysis, etc., play in such a program?
A COE (Center of Excellence) framework seeks to address these aspects and ensure the company can progress on all fronts.
Learn How Memorial Hermann is Using Microsoft Dynamics CRM for Customer Engag...Perficient, Inc.
The presentation will discuss key components of Memorial Hermann’s deployed CRM solution:
Community outreach for potential patients to attract and track their interactions with the hospital, and to ultimately obtain more patients
Specialty group on-boarding process to automate the method of bringing rehab patients into the system for both inpatient and outpatient tracking
Call center technology replacement from an older stand-alone system to a connected CRM system, allowing the hospital to track inquiries concerning events and patient referrals via the phone and online
Max Neeman's Clinical Data Management service has been trusted by numerous global pharmaceutical, biotech and device companies. Renowned for its excellent planning and the utilization of latest technology, the data management team ensures high quality data, quick turnaround time and accelerated solutions for our clients.
Mergers, acquisitions, and partnerships dramatically reducing it consolidati...Health Catalyst
Please join Dale Sanders, President of Health Catalyst Technology, in this webinar as he explains his experiences, observations, and advice about the use of an EDW or DOS to reduce the costs of IT integration in healthcare M&A and rapidly increase the value proposition of the new organization. Dale has a diverse background in complex data environments and decision support, spanning three decades in the US Air Force, National Security Agency, and as a CIO in healthcare.
Learn How ProHealth Care is Innovating Population Health Management with Clin...Perficient, Inc.
Christine Bessler, CIO at ProHealth Care,demonstrates how ProHealth Care became the first healthcare system to produce reports and data out of Epic's Cogito data warehouse in a production environment. In this slideshare, you'll learn:
How they delivered clinically integrated insights to 460 physicians
How access to analytics allows their physicians to easily see which patients need important health screenings or care interventions, setting the stage for enhanced preventive care and better management of chronic diseases
ProHealth Care's strategy to integrate data from Epic with information from other EMRs and data sources to deliver clinically integrated business intelligence
How the organization is positioning itself to deliver against an advanced self-service BI capability in the future
Navigating data strategy is difficult, there are entire books and careers focused on the topic.
For the rest of us that are in need of quick consumable advice, here's a flywheel that articulates the high-level approach our teams are using to create exponential data value for products.
Revolution In Data Governance - Transforming the customer experiencePaul Dyksterhouse
The foundation of managing data security and big data is implementing data governance. Data Owners, Metadata tagging, Customer feedback and Continuous Improvement are critical facets to provide the transparency and consistency so that customer's can trust the data, and make informed decisions.
Business Analytics Competency centre: A strategic Differentiator BSGAfrica
Analytics industry trends and how they relate to the Insurance sector, highlighting the importance of recognising the Customer Lifetime Value (CLV) over the immediate revenue-generation potential of each customer. Steven Ing spoke about data as a strategic business asset, and the importance of recognising it as such. Additionally, he commented on the significance of developing an internal strategic team of experts, with a specific focus on facilitating and promoting the use of analytics to achieve business objectives across the enterprise.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
Building an Analytics CoE (Center of Excellence)Rahul Saxena
This deck is from a workshop I conducted at the Indian Institute of Management, Bangalore (IIMB) on 20th July, 2013.
Agenda:
* What does the organization want to do with analytics? What is the role of the CoE that they envision?
* What is the organizational context? Current providers of analytics? Leadership support?
* What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?
* Where do we stand with analytics capabilities now, compared to what we need?
* How will we evolve the CoE? Set expectations, drive the evolution, establish the value.
Drive Compliance and Profit with Oracle Healthcare AnalyticsPerficient, Inc.
Learn how Oracle's Enterprise Health Analytics (EHA), coupled with Oracle Business Intelligence, speeds the delivery of clinical event reporting by leveraging data integrations to Cerner and the EHA Healthcare Data model.
How EHA integrates EMR and other operational data to provide actionable information with integrity and precision to ready you for the ACO market
How EHA integrates clinical, financial, administrative and research data to speed the time from data input to robust retrospective and predictive analytics
Examples of how Oracle EHA can unlock your EMR data for hospital-acquired conditions and prevention, ad-hoc and standard reporting and other valuable metadata
Data warehouse solutions including strategic roadmaps for Meaningful Use, Population Health Management and Accountable Care
Colliculus Data Research and Analytics | Medical Communications | Business Va...Venugopalarao Boddepalli
Colliculus Data Research and Analytics Services Pvt. Ltd. It’s a fast-paced agency, providing specifically tailored services to Pharma, Biotech, Life Sciences, Medical Device and CRO industries with the team of experienced Medics & qualified professionals. Colliculus emerged as a Medical/ HealthCare KPO outsourcing vendor which focuses on client commitment, consistent quality, and a vibrant internal team culture.
Our Service Offerings:
Medical Writing - Educational, Publication Support, Commercial etc.
Regulatory Writing - Clinical study protocol, Clinical study report, Clinical summaries etc.
Scientific Slidecks - Academic, Product launch, Sales Force training, conferences etc.
Online platform for MSLs & E-learning solutions for sales/product training.
KOL Identification, Mapping and Profiling.
E-learning solutions for sales/product training
Qualitative and Quantitative Healthcare Market Research
Brand Management
Product/brand websites and Mobile App. development.
Clinical Data Management, Statistical Analysis, EDC Support
Conduct CME's, Advisory board meetings, Online/ Offline HCP Certification Programs
Patient Education Services
Medical Information Services
Digital Offerings - 2D/ 3D MOA Videos and other Videos
Our Business Model:
Competitive pricing with cost reduction of 40 to 60%
Resource availability and quick ramp-up
Flexibility to run programs currently not budgeted or with low budgets
Unique and proprietary methodologies consistently deliver high-quality results.
Significant knowledge capture and learning within the dedicated offshore team
We are providing our services to some of the Pharma companies like Sandoz, Mundipharma, MSD, Merck, Dr. Reddy’s, Biological Evans Limited, Pentax Medical etc. and with Healthcare communications / market research companies across the globe.
Kindly reach us for any sort of service requirement or collaboration, we are more than happy to assist you with best possible turnaround options at an earliest.
Contact:
Colliculus Data Research and Analytics Services Pvt. Ltd.
Plot No 8 & 9, 3rd Floor, Vasantha's Cyber View,
Karthika Layout, Near Karnataka Bank,
Madhapur, Hyderabad - 500 081, Telangana, INDIA.
contact@colliculusdataresearch.com | venugopal@colliculusdataresearch.com
+91 40 4019 1852 | +91 7406041119
Thanks for your time !
Moving to the Cloud: Modernizing Data Architecture in HealthcarePerficient, Inc.
Constant changes in the healthcare industry continue to drive innovation in technology and serve as a catalyst for cloud adoption. This trend will continue to evolve and accelerate in the coming years with the increasing need to store and analyze vast amounts of information for personal and population health initiatives.
We joined guest speaker from HIMSS Analytics, James Gaston, to discuss the impact of the cloud on data architecture in healthcare. Topics included:
-The benefits and risks of moving data and analytics environments to the cloud
-Main healthcare use cases for cloud migration
-Deep dive into two leading healthcare organizations’ cloud journeys including drivers, challenges, benefits, and lessons learned
Bundled Payment Changes: Learn What’s New and How to SucceedHealth Catalyst
In January, CMS announced the Bundled Payment for Care Improvement Advanced “BPCI Advanced” program, initiating renewed interest in a total cost of care payment model for specific episodes of care. Regardless of your organization’s current decision to participate, it’s important to understand how bundled payment programs have the ability to significantly decrease your internal costs, broaden your revenue opportunities, and improve patient outcomes across specific populations. The Center for Medicare and Medicaid Innovation’s newest iteration of bundled payments provides another tightly-defined program that allows organizations to scale Population Health Management. Best practice suggests that tactical interventions to assess clinical variation, implement strategic care redesign programs, and to adjust care management-facilitated patient stratification models are important to be successful with bundled payments – so knowing how to implement them is crucial. One organization’s savings is another’s income and without making overhead allocation changes, bundled payments may reduce revenue that has been critically important to maintain hospital profitability. Join this webinar to learn:
* What is new with bundled payments.
* The ramifications bundles can have across organizations.
* Leveraging data and strategic analysis to identify opportunities for bundled payment success.
* Operationalizing successful care program tactics to be successful in bundled payment contracts.
Executive BI, Analytics, Modeling and Insights Strategy Framework PracticesInsightSlides
This presentation looks at the frameworks Executives need to consider in their BI, Analytics, Modeling, and Insights Strategies.
This include frameworks on BI, Analytics. Insights and Modeling strategy creation, strategy development, capabilities, considerations, proven strategy practices, operating models and opportunities.
The Analytics COE positioning your business analytics program for successKiran Garimella
You should consider the following three aspects of your Business Analytics Program:
* The Business (not just data science, big data, and technology)
* Analytics as the DNA of the company (and not just a competency of an elite few)
* A Programmatic approach that sustainable for the life of the company (and not just a one-time project or initiative)
What role do classical statistics, Bayesian statistics, judgment under uncertainty, heuristics, biases, categorical data analysis, etc., play in such a program?
A COE (Center of Excellence) framework seeks to address these aspects and ensure the company can progress on all fronts.
Learn How Memorial Hermann is Using Microsoft Dynamics CRM for Customer Engag...Perficient, Inc.
The presentation will discuss key components of Memorial Hermann’s deployed CRM solution:
Community outreach for potential patients to attract and track their interactions with the hospital, and to ultimately obtain more patients
Specialty group on-boarding process to automate the method of bringing rehab patients into the system for both inpatient and outpatient tracking
Call center technology replacement from an older stand-alone system to a connected CRM system, allowing the hospital to track inquiries concerning events and patient referrals via the phone and online
Max Neeman's Clinical Data Management service has been trusted by numerous global pharmaceutical, biotech and device companies. Renowned for its excellent planning and the utilization of latest technology, the data management team ensures high quality data, quick turnaround time and accelerated solutions for our clients.
Mergers, acquisitions, and partnerships dramatically reducing it consolidati...Health Catalyst
Please join Dale Sanders, President of Health Catalyst Technology, in this webinar as he explains his experiences, observations, and advice about the use of an EDW or DOS to reduce the costs of IT integration in healthcare M&A and rapidly increase the value proposition of the new organization. Dale has a diverse background in complex data environments and decision support, spanning three decades in the US Air Force, National Security Agency, and as a CIO in healthcare.
Learn How ProHealth Care is Innovating Population Health Management with Clin...Perficient, Inc.
Christine Bessler, CIO at ProHealth Care,demonstrates how ProHealth Care became the first healthcare system to produce reports and data out of Epic's Cogito data warehouse in a production environment. In this slideshare, you'll learn:
How they delivered clinically integrated insights to 460 physicians
How access to analytics allows their physicians to easily see which patients need important health screenings or care interventions, setting the stage for enhanced preventive care and better management of chronic diseases
ProHealth Care's strategy to integrate data from Epic with information from other EMRs and data sources to deliver clinically integrated business intelligence
How the organization is positioning itself to deliver against an advanced self-service BI capability in the future
Navigating data strategy is difficult, there are entire books and careers focused on the topic.
For the rest of us that are in need of quick consumable advice, here's a flywheel that articulates the high-level approach our teams are using to create exponential data value for products.
Revolution In Data Governance - Transforming the customer experiencePaul Dyksterhouse
The foundation of managing data security and big data is implementing data governance. Data Owners, Metadata tagging, Customer feedback and Continuous Improvement are critical facets to provide the transparency and consistency so that customer's can trust the data, and make informed decisions.
Business Analytics Competency centre: A strategic Differentiator BSGAfrica
Analytics industry trends and how they relate to the Insurance sector, highlighting the importance of recognising the Customer Lifetime Value (CLV) over the immediate revenue-generation potential of each customer. Steven Ing spoke about data as a strategic business asset, and the importance of recognising it as such. Additionally, he commented on the significance of developing an internal strategic team of experts, with a specific focus on facilitating and promoting the use of analytics to achieve business objectives across the enterprise.
Expert data analytics prove to be highly transformative when applied in context to corporate business strategies.
This webinar covers various approaches and strategies that will give you a detailed insight into planning and executing your Data Analytics projects.
Building an Analytics CoE (Center of Excellence)Rahul Saxena
This deck is from a workshop I conducted at the Indian Institute of Management, Bangalore (IIMB) on 20th July, 2013.
Agenda:
* What does the organization want to do with analytics? What is the role of the CoE that they envision?
* What is the organizational context? Current providers of analytics? Leadership support?
* What will the Analytics CoE need to be like (now and in the future, up to the planning horizon)?
* Where do we stand with analytics capabilities now, compared to what we need?
* How will we evolve the CoE? Set expectations, drive the evolution, establish the value.
Drive Compliance and Profit with Oracle Healthcare AnalyticsPerficient, Inc.
Learn how Oracle's Enterprise Health Analytics (EHA), coupled with Oracle Business Intelligence, speeds the delivery of clinical event reporting by leveraging data integrations to Cerner and the EHA Healthcare Data model.
How EHA integrates EMR and other operational data to provide actionable information with integrity and precision to ready you for the ACO market
How EHA integrates clinical, financial, administrative and research data to speed the time from data input to robust retrospective and predictive analytics
Examples of how Oracle EHA can unlock your EMR data for hospital-acquired conditions and prevention, ad-hoc and standard reporting and other valuable metadata
Data warehouse solutions including strategic roadmaps for Meaningful Use, Population Health Management and Accountable Care
Colliculus Data Research and Analytics | Medical Communications | Business Va...Venugopalarao Boddepalli
Colliculus Data Research and Analytics Services Pvt. Ltd. It’s a fast-paced agency, providing specifically tailored services to Pharma, Biotech, Life Sciences, Medical Device and CRO industries with the team of experienced Medics & qualified professionals. Colliculus emerged as a Medical/ HealthCare KPO outsourcing vendor which focuses on client commitment, consistent quality, and a vibrant internal team culture.
Our Service Offerings:
Medical Writing - Educational, Publication Support, Commercial etc.
Regulatory Writing - Clinical study protocol, Clinical study report, Clinical summaries etc.
Scientific Slidecks - Academic, Product launch, Sales Force training, conferences etc.
Online platform for MSLs & E-learning solutions for sales/product training.
KOL Identification, Mapping and Profiling.
E-learning solutions for sales/product training
Qualitative and Quantitative Healthcare Market Research
Brand Management
Product/brand websites and Mobile App. development.
Clinical Data Management, Statistical Analysis, EDC Support
Conduct CME's, Advisory board meetings, Online/ Offline HCP Certification Programs
Patient Education Services
Medical Information Services
Digital Offerings - 2D/ 3D MOA Videos and other Videos
Our Business Model:
Competitive pricing with cost reduction of 40 to 60%
Resource availability and quick ramp-up
Flexibility to run programs currently not budgeted or with low budgets
Unique and proprietary methodologies consistently deliver high-quality results.
Significant knowledge capture and learning within the dedicated offshore team
We are providing our services to some of the Pharma companies like Sandoz, Mundipharma, MSD, Merck, Dr. Reddy’s, Biological Evans Limited, Pentax Medical etc. and with Healthcare communications / market research companies across the globe.
Kindly reach us for any sort of service requirement or collaboration, we are more than happy to assist you with best possible turnaround options at an earliest.
Contact:
Colliculus Data Research and Analytics Services Pvt. Ltd.
Plot No 8 & 9, 3rd Floor, Vasantha's Cyber View,
Karthika Layout, Near Karnataka Bank,
Madhapur, Hyderabad - 500 081, Telangana, INDIA.
contact@colliculusdataresearch.com | venugopal@colliculusdataresearch.com
+91 40 4019 1852 | +91 7406041119
Thanks for your time !
Moving to the Cloud: Modernizing Data Architecture in HealthcarePerficient, Inc.
Constant changes in the healthcare industry continue to drive innovation in technology and serve as a catalyst for cloud adoption. This trend will continue to evolve and accelerate in the coming years with the increasing need to store and analyze vast amounts of information for personal and population health initiatives.
We joined guest speaker from HIMSS Analytics, James Gaston, to discuss the impact of the cloud on data architecture in healthcare. Topics included:
-The benefits and risks of moving data and analytics environments to the cloud
-Main healthcare use cases for cloud migration
-Deep dive into two leading healthcare organizations’ cloud journeys including drivers, challenges, benefits, and lessons learned
The Path to Data and Analytics ModernizationAnalytics8
Learn about the business demands driving modernization, the benefits of doing so, and how to get started.
Can your data and analytics solutions handle today’s challenges?
To stay competitive in today’s market, companies must be able to use their data to make better decisions. However, we are living in a world flooded by data, new technologies, and demands from the business for better and more advanced analytics. Most companies do not have the modern technologies and processes in place to keep up with these growing demands. They need to modernize how they collect, analyze, use, and share their data.
In this webinar, we discuss how you can build modern data and analytics solutions that are future ready, scalable, real-time, high speed, and agile and that can enable better use of data throughout your company.
We cover:
-The business demands and industry shifts that are impacting the need to modernize
-The benefits of data and analytics modernization
-How to approach data and analytics modernization- steps you need to take and how to get it right
-The pillars of modern data management
-Tips for migrating from legacy analytics tools to modern, next-gen platforms
-Lessons learned from companies that have gone through the modernization process
Square Pegs In Round Holes: Rethinking Data Availability in the Age of Automa...Denodo
Watch full webinar here: https://bit.ly/43qJKwn
Data-led transformations are becoming more prevalent in recent years, across numerous industries. More and more senior leaders are looking for data to drive their business decisions and impact their bottom line. One key challenge facing such businesses is the ability to pivot to new technologies while maintaining investments in legacy systems they have grown to rely on. In an age where automation, internet-scale search, and advanced analytics are driving many new advances, it is important to understand that this is not only a pivot in terms of technologies, it is a pivot in terms of how we think about and utilize data of different types. Traditional systems since the 1970’s have been built around database concepts where data is physically pipelined, mapped together, statically modeled, and locked away in vaults. The types of vaults have evolved over time from basic databases, to data warehouses, to data lakes, to lake houses, and so on.
The fundamental premise remains: data is placed into sealed containers, such that the critical approach is around storage, instead of being aimed at retrieval. Reversing this approach can, instead, lead to understanding data as transient, on-demand, and immediately available to end users within a certain context. This talk will discuss certain contemporary concepts that are expanding the notion of data storage devices and, instead, are moving to loosely connected data retrieval devices, or in some cases, data generation devices. We will examine this shift in approach and what it means for designing and deploying new types of technologies that can be more flexible and provide improved business value for clients in the fast-paced evolving world of Artificial Intelligence.
Guided Analytics vs. Self-Service BI: Choose Your Path to Data-driven Success!Polestar Solutions
Empower your organization with the right analytics approach—Guided Analytics or Self-Service Business Intelligence (BI)—to unlock the true potential of your data. Discover the benefits and find your perfect fit, whether you prefer expert-guided insights or self-exploration, enabling your team to make data-driven decisions and drive transformative outcomes.
Microsoft: A Waking Giant in Healthcare Analytics and Big DataDale Sanders
Ten years ago, critics didn’t believe that Microsoft could scale in the second generation of relational data warehouses, but they did. More recently, many of these same pundits have criticized Microsoft for missing the technology wave du jour in cloud offerings, mobile technology, and big data. But, once again, Microsoft has been quietly reengineering its culture and products, and as a result, they now offer the best value and most visionary platform for cloud services, big data, and analytics in healthcare.
Active Governance Across the Delta Lake with AlationDatabricks
Alation provides a single interface to provide users and stewards to provide active and agile data governance across Databricks Delta Lake and Databricks SQL Analytics Service. Understand how Alation can expand adoption in the data lake while providing safe and responsible data consumption.
Big data journey to the cloud maz chaudhri 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
How to classify documents automatically using NLPSkyl.ai
About the webinar
Documents come in different shapes and sizes - From technical documents, customer support chat, emails, reviews to news articles - all of them contain information that is valuable to the business.
Managing these large volume data documents in a traditional manual way has been a complex and time-consuming task that requires enormous human efforts.
In this webinar, we will discuss how Machine learning can be used to identify and automatically label news articles into categories like business, politics, music, etc. This can be applied in another context like categorizing emails, reviews, and processing text documents, etc.
What you will learn
- How businesses are leveraging document classification to their advantage
- Best practice to automate machine learning models in hours not months
- Demo: Classify news articles into the right category using convolution neural network
Keynote from Big Data World Show Singapore, April 2015.
• How is data driving change?
• Where are the opportunities, across industries?
• What is required to gain value from data?
• How can you get started today?
20 Years in Healthcare Analytics & Data Warehousing: What did we learn? What'...Health Catalyst
The enterprise data warehouse (EDW) at Intermountain Healthcare went live in 1998. The EDW at Northwestern Medicine went live in 2006. Dale Sanders was the chief architect and strategist for both. The business inspiration behind Health Catalyst was, in essence, to create the commercial availability of the technology, analytics, and data utilization skills associated with these systems at Intermountain and Northwestern. Lee Pierce assumed leadership of the Intermountain EDW in 2008. Andrew Winter assumed leadership of the Northwestern EDW in 2009, and transitioned leadership of the EDW to Shakeeb Akhter in 2016. This webinar is a fireside chat among friends and colleagues as they look back across their healthcare IT decisions to answer these questions:
What did we do right and what did we do wrong?
What advice do we have for others in this emerging era of Big Data?
What does the future of analytics and Big Data look like in healthcare?
Big Data Analytics for Healthcare Decision Support- Operational and ClinicalAdrish Sannyasi
Splunk’s data analytics platform could be utilized to solve many high impact business problems in healthcare delivery systems to reduce cost, improve patient outcome and safety, and enhance care coordination experience. Analyze observed behavior from healthcare event data and metadata to discover patterns, monitor compliance, and optimize the workflow. Furthermore 80% of healthcare data is unstructured (clinical free text and documentation), or semi-structured and many new data sources are such as tele health, mobile health, sensors, and devices are getting integrated in many healthcare systems specifically in the area of chronic disease management. So, one need analytics software that can harvest, interpret, enrich, normalize, and model diverse structured and unstructured data and analytics approaches that embrace the “data turmoil” by relying less on standardized data items and more on the capability to process data in any format.
Part 2 - 20 Years in Healthcare Analytics & Data Warehousing: What did we lea...Health Catalyst
Lessons learned over 20 years. This time we focus on technology lessons learned from experience at Intermountain Healthcare, Northwestern Medicine and Cayman Islands Health Authority
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
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About Auckland District Health Board
Introduction 2
• Auckland District Health Board (ADHB) serves around 10 per
cent of the country's population
• Provider of primary, secondary, tertiary and quaternary
services for around 1.6 million people in the northern region
• Regional and national centre of excellence
Auckland
Hospital
Greenlane Clinical
Centre
Starship Childrens
Hospital
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Professional Background DHB Responsibilities Personal
Flat : 40 km/hr
Downhill : ??
Introduction
About me
• 20+ years in Technology and Data
• Enterprise transformation and data
migration projects
• Data governance implementations
• Industry data models
• Pervious life - Design and development
of n-tier web applications and solutions
• Intelligence, Analytics, Data
governance, Data quality & Data
architecture
• Data Strategy for ADHB
• Regional - Architecture group, Data
design authority, HIP Steerco, DSI
Working Group
• National – Integration Steering
Committee
• Sci-fi junkie
• Avid e-scooter rider
3
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Health systems have recognised connected data across care settings is key to this transformation
Advances in Data and Analytics are creating new opportunities to
change how healthcare services are provided
4
The public health system will be shifting, from a
sometimes fragmented health and disability system with
a siloed service models, to a more connected and
whānau-centric approach (Health and Disablity System
Review March 2020).
Data and analytics are essential to making the
community, patient and whānau experience transparent
and to informing system redesign and that will also
improve performance.
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At ADHB we are starting to use previously inaccessible data by applying new technologies
Using data in new ways through new capabilities is allowing ADHB to
gain better clinical and operational insights
5
Radiology data analysis
Radiology – Chest Nodule Detection
Care Navigation – Digital Workflow Tool
Workflow data as a patient story
Equity Focused Planned Care Response
AED hourly presentations forecasting
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Analysis of our backlog of business requests shows that most business demand was focussed on the
left hand side of the analytics spectrum
However, one of the biggest growth areas is self-service analytics, the provision
of data and analytics capabilities for business users to develop their own
intelligence - when they need them
6
Analytics Spectrum
20-30% of demand
High Cost, High Repeatability, Gold
Quality
70-80% of total demand
Low Cost, High Variability,
Many One-off Insights
Management /
Performance
Strategic /
Compliance
Data Science
Ad-hoc Data
Analysis,
experimentation,
Research
Operational
Reporting
Operational
Analysis
Traditional Business
Intelligence Sweet Spot
Sweet Spot for Self-Service
Analytics
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Business teams safely and securely use their data and the latest tools to build new insights and drive
innovation.
The Opportunity: By enabling business users to safely access and use their data in secure
dedicated environments, with supporting tools and environments, we can significant
increase the value business users derive from their data
7
PICU
Peri-
Operative
Labs Raw Data
Curated Data
Operational Data
Store
Enterprise Data
Warehouse
Data Marts
Security
&
Auditing
Data
Governance
(Data
Catalogue)
Advanced Analytics Models
OLAP / Semantic Models
Sandboxes /
Playpens
Data
Data
Data
Business
Intelligence
Tools
Data
Integration
Tools
Enterprise
Data
Catalogue
Each sandbox area is equipped with:
• Data storage for the temporary persistence
of data.
• Data integration tools to transform data.
Business users can still use database
constructs such as stored procedures to
write code.
• Business intelligence tools to develop
reports if needed.
• A data catalogue to explore and request
access to data.
• Utilities to automatically dispatch data to
sandboxes.
• Built-in security and audit capabilities to
track what data is being used and by whom.
A “Citizen Data Science”
example – where the
CLABs (central line
associated bacteraemias)
in the quarter a cluster or
not
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The most difficult part is the change in data culture which needs to be supported by an operating model
that feeds and grows the self-service eco-system
ADHB’s self-service model adopts a holistic approach to foster the growth and
value of this capability
8
2. Operating
Model
Modern
Intelligence
Paradigm
3. Tools &
Technology
1. Data
Culture
Data Culture
Operating Model
Tools & Technology
Enable the army of citizen analysts, scientists and engineers to quickly discover the
data they need to make decisions. Data & intelligence teams will transition to a
model of co-delivery where they work closely with business teams, enabling them to
use the tools of their choice to get the insights they need.
Reconfiguration of our data and intelligence teams, with new capabilities added
to lift productivity, improve the quality of interactions with business teams and
speed of delivery.
We also need to make changes to our existing technology, continuing the rollout
of PowerBI but also add new capabilities to accelerate data delivery.
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Each component has a synergy and dependency on the other making this a compelling model that can
work for all different types of users
Data Culture: We have defined data culture as 3 key components 9
Data
Literacy &
Capability
Inquisitive
Workforce
Data &
Tools
Ability to discover any data in our
systems (on premise or cloud)
Getting approvals quickly to use data
The tools and data environments
needed to safely and securely use any
type and size of data
Curious about observed patterns and willing to
dig a bit deeper
The desire to use detailed insights before
making decisions
Willing to learn new skills
Understanding the data and what
it means
Ability to decipher insights and
their business context
Sufficient technical skills to
manipulate data to create relevant
insights
enables the use of
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Our data use framework combines fine grain access controls and audit & monitoring capabilities to
maintain the safety of our valuable health data. Our end-users sign up to a data use contract and are
trained to use data safely and understand their obligations.
Tools & Technology: Safe use of data is the biggest challenge and potential
roadblock for self-service
14
Data,
Technology
& Security
Controls
Auditing &
Monitoring
Privacy & Security,
Ethics &
Consent
Delivery, Support
& Training
ADHB
Self-Service
Framework
1. Security Roles & Membership (who is
in what role)
2. Monthly Access sign-off (deltas)
3. Data Governance Forum (Business
Owners, Data Stewards)
1. ADHB Privacy and Security Policy
2. PowerBI Admin User terms and
conditions
3. Privacy Impact Assessment
4. Data Classification (applied to data
and reporting)
5. Staff Confidentiality Agreement
6. Self-Service User Agreement
7. Data Access Request Form
1. Auditing and Monitoring of access rights
2. User access history (reports, datasets, tables)
3. Data Access Reporting
1. Training / On-boarding
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These personas have been tested with end users and continue to be refined and optimised as our
technical environments evolve
Operating Model: We have aligned our service offerings to a set of business
personas (Gartner)
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INFORMATION PANEL
01
70%
SS users
Interaction
with content
Data literacy
Technical Skill 5% 50%
Info Consumer Info Explorer Citizen Analysts Citizen Data Scientist
ANALYTICS WORKBENCH
02
DATA SCIENCE LAB
03
Duplícate & modify
Able to nominate their
content
Unable to self validate their
work
Literate
Added ability to bring in new data to
“Sandbox”.
Able to promote their content
Able to self-validate and validate
work of others
Fluent - Multilingual
50% 75%
25% 5%
Content query
usage
Consume & Interact
No formal content
creation rights
Unable to validate or
nominate any new
content.
Conversational
Can build prototypes. Using “Sandbox”. Brings in domain-
specific data, flat files or third party data to enhance
analysis.
Able to nominate their content
Able to validate work of others
Competent
Validation of
work
Citizen Developer
Consumer Explorer Innovator Expert
25%
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These capabilities allow a wider range of staff within directorates to
develop deeper insights - quickly
12
Decision Maker /
Information
Consumer
Information
Explorer
Citizen Analyst
Citizen Data
Developer
Citizen Data
Scientist
Key Activities
Technical Skills
Required
Tools Used
• View prebuilt reports • View prebuilt reports
• Slice and dice intelligence
reports
• Create and run excel pivot
tables to explore data
• Build new SQL queries to
interrogate data
• Build PowerBI Reports
from datasets
• Publish new reports
• Write complex code to
transform data
• Develop deterministic
models
• Prototype new
intelligence outputs
• Build analytical models
using statistical and
programmatic
approaches
• None • Excel pivot tables and
pivot charts
• PowerBI Development
• SQL Code
• PowerBI development
• SQL Scripting &
procedures
• Lightweight programming
(e.g. HTML, JavaScript)
• R / Python
• Advanced SQL coding
• Lightweight programming
(e.g. HTML, JavaScript)
• Web browser • Excel
• PowerBI Web (optional)
• PowerBI Desktop
• PowerBI Web
• SQL Management Studio
(or similar)
• PowerBI Desktop
• SQL Management Studio
(or similar)
• R Studio
• PowerBI Desktop or
similar
• SQL Management Studio
(or similar)
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Analysts in directorate teams can prototype new datasets to build deeper insights.
If required, these can be optimised by HIT and released into production.
13
How does it work?
1) HIT uses our new Self-Service data
generation engine to create business
and analyst data views (simple excel
like views). These views remove all
complexities of joining data from
different systems
2) The business data views are
published as PowerBI data sets
3) PowerBI reports and dashboards are
generated using 1 or more PowerBI
data sets
4) Business Intelligence analysts (or
similar) in the business can generate
new insights by :-
a) Creating new reports using
PowerBI Datasets
b) Adding data to existing business
data views and publish new
PowerBI datasets (manual)
c) Create brand new business data
views using analyst data views,
business data views and/or raw
source system data views
Analyst
Playpen
• Business data views
• Analyst data Views
• Raw source system data
Source Systems
e.g. CMS,
Safer sleep
Data Warehouse
(Titan)
new
Import
PowerBI
Data Sets
Self-
Service
Engine
Enterprise Datasets –
Generated by
HIT SS Engine
Prototype +
Ad0hoc insights
Convert Prototype
insights into Enterprise
Directorate Staff
Use playpen to build new insights using :-
• Additional data from Titan
and source systems
• Import custom data from
spreadsheets & external sources
• Write SQL to build new views
HIT Data & Analytics team-
• Creates new libraries of simplified
views joining data from systems as
directed by customers
• Implements processes to publish
data to PowerBI data sets on a
regular basis (daily, hourly etc)
• Implement security and monitoring
to ensure data usage is governed
PowerBI
Visualisations
Microsoft Excel
Pivot tables and
charts
new
new
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To create a self-serve “Plug & play” model of consuming data and analytics, we are pivoting our internal
teams into a different set of capabilities. This is enabling us to unlock value that sits within business
teams that an IT centric delivery model cannot realise
Operating Model: Our hybrid operating model wraps the core capabilities into
directorate specific capabilities
14
Supported by a hybrid operating Model
Current – Centralised
With Informal federated delivery
Future – Managed
hybrid delivery model
An intelligence capability model
A modern Intelligence paradigm
enabling pillars
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A traditional capability vertical ensures our team develop high levels of competence in their area of
expertise. The focus on outcomes is provided by delivery squads which we recalibrate on a regular basis
Operating Model: Within the data & analytics, we have organised our delivery
functions into 2 layers
15
Maintaining structures aligned with our core
capabilities to increase competence and capability
Organised into self-organising teams (relatively) with a focus
a clear set of objectives and outcomes (Porter’s model)
Self-Service
Delivery
Squads
Projects Automation
Clinical
Databases
Data
Management
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We have some of the building blocks already but are slowly investing in missing capabilities
16
Tools & Technology: We are acquiring and implementing a new range of tools to
build the foundations of frictionless self-service environments
Data
Virtualisation
Data
Visualisation
Data Movement
& Transformation
Data Quality
Management
Data
Catalog
CDC /
Replication
Workflow
Management
Data Visualisation
ADHB have PowerBI, which is a leading data visualisation and analysis tool. Additionally, existing
toolsets like SAP Business Objects, SAP Lumira and Excel offer a range of options for end users.
Workflow Management
With the acquisition of ServiceNow, Microsoft Office 365 and Azure,
we have all the tools we need to implement workflow management.
Data Movement & Transformation
ETL tools are normally used to extract, transform and load data. Our investment in WhereScape RED will need to
be reviewed overtime given the recent vendor acquisition and unmet demand for a higher capability toolset to
support data access from/to cloud based applications.
CDC / Data Replication
The ability to replicate all or part of any database within our eco-system is badly missing at ADHB and
required immediately to decrease the cost and time taken to provision new data to end-users. This
capability will also minimize time and effort needed to integrate data from cloud based systems.
Data Virtualisation
Data virtualization enables all data to come together without having to use complex and expensive ETL
procedures to physically move the data into one place. In other words, the data stays in its original location, but
you can query it just as if it was local. Some of this capability exists within newer versions of existing tools.
Data Catalog
The ability to find data located in any system regardless of where it sits. This is a big gap within our eco-
system and needs to be addressed urgently.
Data Quality Management
As the quality of data is better understood through the use of a data catalog, tools to monitor
and fix data quality can be purchased. The HARP transformation program would benefit
significant from a data quality and profiling tool.
Tools to needed enable self-service
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Tools & Technology: Within the self-service environments, data is organised
into several layers allowing the different personas to operate
17
Analyst
Playpen
Business
Views &
Analyst Views
Raw Data
Subsets
Data store for end users to transform data
Users can also create and run analytical models
New data can be uploaded by end-users directly
Read-only access for end-users
Simplified business views organised as a cube
Business Views are organised by subject areas within data
Maintained and governed by HIT
LABS
Mental
Health
Periop Others
Read-only access for end-users
Approved subsets of raw copy of source system data
Data refreshed on agreed calendar and reconciled
Maintained and governed by HIT
Data sourced from source systems for multiple uses
Uses include EDW provisioning, data Science, data quality
management, digital systems Consumption etc
Dedicated and secure PowerBI workspaces
Users can refresh report data from all 3 layers below
Users can build and share new reports
Visualisation /
Presentation
Layer
Source System Data
Raw Copy
Working space
for end-users
Workspace/Directorate
specific data subsets
(dedicated for
self-service)
Shared Raw Copy
(also used for other
purposes)
End-user managed
supported by Self-Service Squad
Managed by D&A
Self-Service Squad
Managed by D&A
Engineering team in partnership
with healthAlliance
LABS
Mental
Health
Periop Others
LABS
Mental
Health
Periop Others
LABS
Mental
Health
Periop Others
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They also help us govern environments, ensuring we continue to meeting our obligations to patient data
Our data stewards are our self-service champions in the business and
are supporting adoption within their directorates
Patient
Day / Inpatient
S
O
Patient
Outpatient
S
O
Patient
Theatres
S
O
Clinical Coding
S
O
Clinical Records
S
O
Radiology
S
O
Laboratories
S
O
Child Health
S
O
Ophthalmology
S
O
Community
S
O
Mental Health
S
O
Pharmacy
S
O
Human Resources
S
O
Finance
S
O
Women’s Health
S
O
17
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Our data governance function has been instrumental in gaining
support and approval to proceed
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Digital Steering
Committee
Data Governance Support
Office
Data Stewardship
Council
Working
Group(s)
Information Governance
& Privacy Group
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We have also opened up a range of new opportunities for our teams to focus on in 2021
Progress: With self-service, we have increased the value being delivered by the
D&A team across the DHB
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Self-Service Implementation
(Stage 1)
In-Progress
• Labs Self-Service
• PICU
• Perioperative
• HR (PowerBI Only)
• Cardiology (PBI Only)
Operational Data Store (temporary)
• Lab demand optimisation
• Women’s Health IOC Dashboard
(initial)
Stage 1 – Extended (information
explorer, consumer only)
• Production Planning (initial)
• Performance Improvement (Planned
Care scorecard)
• Outpatient (DNA Reporting)
• Mental Health (Patrick)
• Allied Health (Joe Monkhouse)
• Adult Long Term & Community (BAU
Backlog)
• Clinical Coding (diagnoses)
• Child Health Excellence
Cloud Data Environment &
Tools
Stage 2 – Self Service
• Women’s Health
• Quality & Safety (Jenny)
• Radiology (Nicola)
• Finance (Nicki Hill)
• Cancer & Blood (Ben Lawrence)
• Pharmacy (tbc)
• Ophthalmology (tbc)
• Community (tbc)
• ACC (tbc)
Data Warehouse / ODS (Cloud)
• Lab demand optimisation
• Quality data mart (tbc)
• Production Planning Reporting
• Healthcare Logic / SFN (tbc)
• IOC – Women’s Health
• Hospital IOC extensions
Digital
• Service Now (ODBC)
• Single View
Production Data Analytics
Implementation
POC’s
• Sleep Studies
• Radiology AI
• Others
Single View
• Single view of patient
• Production Planning Analytical
models
• Integrated pathways data (prod
planning)
Clinical Database
Design & Implementation
Confirmed Demand
• Enterprise Dendrite
• Dendrite Multi-site Registries
• Redcap Implementation
• Edge Data Integration
• Edge BI Reporting
Data API’s / Micro-Services
Confirmed Demand
• Service Now Data API’s
• Clinical Trial Mgmt API’s
• Clinical Audit Data API’s
• Clinical Research API’s
HIT Portfolio Demand
• SNOW Digital Apps requiring Data
e.g. planned care projects
• Data supply to key apps e.g. e-orders,
SMT, CarePathways etc where
appropriate
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Cloud Data Staging Layer
Our citizen workforce will lead the development valuable new insights which can be deployed across
various parts of our data environments
The Future: As our self-service environments are mature, business led data projects will
provide relevant content for the rest of our data environments
21
Older/delicate DHB
Source Systems
Raw Data Staging Layer
On-Premise
Cloud
Newer DHB
Source Systems
Cloud Raw Data (Structured)
PowerBI
Workspace
Operational
Data Stores
DevOps
CI/CD
GitHub
Management
Console
Fast Data
Cache
(COSMOS /
Redis/Mem
cache)
API Gateway & Catalog
Batch Load,
Micro Batch
Streaming
Batch,
Micro batch
Cloud Raw Data (Unstructured)
Playpen
(for self-
service)
Reconciliation
MDM
(single views
of …)
Container
Management
for Analytics &
Microservices
EDW
Analytical
Datasets
Micro Batch
Streaming
Medical Devices,
Data Lake
Batch, Micro Batch, Streaming
Data Catalog
Data Profiling