Nik Molley 1 21 15

Host: Matt Barnewall

Nicholas Molley is an IBM-certified Senior Consultant and Information Architect in the Software Group (SWG) Health Care practice. The practice is responsible for providing enterprise information management solutions to academic medical research centers (AMRC), research and teaching hospitals, and private corporations involved with health care information systems. He has more than twenty years of experience in strategic and technical consulting. Prior to joining IBM, Nicholas was a Practice Director at Price-Waterhouse-Coopers (PwC).

Nicholas holds an MBA in Systems Management (Baldwin-Wallace Univ.) and has completed advanced studies in Management Information Decision Systems (Case-Western Reserve Univ.). He is a member of the Adjunct Faculty at two colleges where he teaches both graduate and undergraduate courses for the departments of Mathematics/Computer Science and Business Administration. He is also a faculty member for the Cleveland Clinic’s Samson Global Leadership Academy. The Academy delivers executive education by pairing Cleveland Clinic physicians with health care thought leaders from academia.

Nik Molley will be talking on the following subjects
1. Big Data and Analytics in Healthcare
2. Concept of a Reference Architecture
3. Healthcare Reference Architecture
4. Delivery Methodology

NOTE: Nik Molley will be demonstrating a new Watson-based tool for us on Friday. He told me today that if we bring in an Excel file of data, he will use it to demonstrate the tool. If you have a data set that we could use, please make the class aware of it.

Presentation: Big Data and Analytics Reference Architecture: Healthcare Industry

Architecture: Overarching framework for an organization to build on

  • Customers look for architecture not a solution

Analytics: The processes and procedures performed on big data to gain insight

  • Goals: lower cost, improve outcomes

How do you build an architecture?
Client Time Varies: 3-12weeks

  1. Understand Client-Business Drivers: What do you need? Consumer demands
    • example business driver: provide increased access to healthcare
  2. Define Client Requirements
    • User Cases
    • Functional Requirements: Things the architecture must do
    • Non-Functional Requirements: Things the architecture does not have to do but worry about, ie, security and performance
  3. Design Solution
    • System context
    • Architecture overview
    • Technology Brief
  4. Detail Design to Define BOM
    • Architecture Decisions
    • Operational Model
  5. Best Practices Dev OPs
    • Best Practices: reuse components of design process
    • Dev Ops

Data Scientist: sift through all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem

Architecture Overview: Data and Analytics
Transaction data: data collected while doing business (operational data)
Data warehouse: Database that has data that can be strategic (aggregate data)

  • Software and procedures to discover hidden insignt

Dimensional: Same as warehouse except different audience (less CS background)
Analytic: Done by data scientist, find insight on lots of data with tools

Put the data where
Big data repository: dumping ground for data (data warehouse)
Data marts: subsets of warehouses
Actionable insight: User community
Common Processes

  • Governance: be able to manage everything in repository
  • Security: who has acess
  • Platforms: hardware

Streaming Computing: data in real time to discover (SPL: Stream programming language)

  • Data Baby: monitor baby vital signs to predict infection 48 hours in advance
  • Smarter Cities: Cars talk to other cars, real time data to change (lights, gps, ect.)

Key Decision Areas

  • Performance
  • Sacalability: getting larger, law of large numbers
  • Financial decision
  • Reliability
  • Backup and Restore: Files backed up in case of deletion
  • Sensitive data: who has access and what can they do
  • Disaster Recovery: Systems mirror each other to keep from whole business going down

Implementation Best Practices: Different from each organization
Deployment Best Practices

Data Reservoir Logical Architecture
"Data's the new oil"
Wearable data
Unstructured data

Data Self Service: keep IT out of getting data (big deal)

  • anybody can do anything (problem)
  • anybody has access (good thing)


You get exposure to building architecture at first but are not hired into it as that position?

  • Entry level: shadowing position for first few years (shadows and mentor)
    • Only there to observe and learn process
    • Get insight into the industry. What is important?
    • Learn how to do architecture

The medical company had a past architecture?

  • Documentation is a big deal
  • No they didn't, basic systems created and evolved over time
    • This is not a good practice
    • Architecture is designed for the long term

Associate consultant: resume builder

  • no acutal projects to deliver on at first
  • Never by yourself- always a team engagement student-entry level jobs

Follow Up Questions

1.) In the step of the TeamSD methodology titled "Detail Design to Define BOM," what is BOM?
BOM = bill of materials - basically, this is a specification of components needed to build something, whether is a house or a car or a piece of software.

2.) When did Watson become finished and start being used by businesses?
Also, Watson technology is continually evolving so it's really not in a "finished" status. For example, subsequent releases of Watson will include sensory capabilities. That said, there is sufficient capability already built that can be used by businesses. Most industry-specific application of Watson started in 2013.