data and analytics - revolution or evolution? · hadoop: mapreduce & hdfs, nosql, in memory...

Jote Taddese IT Strategy Adviser at

Medtronic

Data and Analytics - Revolution or Evolution?

Marina KerbelEA Consultant at Medtronic

Principal at UpOnData

November 8, 2018

A LEGACY OF INNOVATION —TAKINGHEALTHCARE FURTHER, TOGETHER.

3

OVERVIEW OF MEDTRONIC OUR DIVERSE PORTFOLIO

RESTORATIVE THERAPIES GROUP

BILLION$7.4

MINIMALLY INVASIVE THERAPIES GROUP

BILLION$9.9

CARDIAC AND VASCULAR GROUP

$10.5BILLION

DIABETES GROUP

BILLION$1.9

$29.7BILLIONFY17TOTALREVENUE*

* Information based on Medtronic FY2017 reporting.

$29.7

$16.6 $17

$20

IN BILLIONS

$28.8

2013 2017201620152014

6

WE DARE TO DREAM…

“Imagine a World where Information provides actionable awareness to Predict, Detect and Prevent the occurrences of

all diseases and Save Lives.”

In the world of digital business – Information is Permanent!Technologies Come and Go.

7

Unprecedented Pace of Changes

http://mattturck.com/bigdata2018/

Example - Big Data and AI Landscape from FirstMark

8

~1990s ~2010 ~2018 +

Accelerating Data Changes

EDW

Interconnected Intelligent Enterprise

Big Data

Advanced Analytics

~2015

Rate of

Changes

Key Changes

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Sources Data Systems Consumers

Enterprise Relational Data

CRM

ERP

Enterprise Reporting

Applications

Batch

Batch

Integrated Enterprise Data

Key Skills: Data Analysis, SQL, Modeling, Database Administration, ETL Development, Reporting

~1990s - Data Warehouse

EDW

10

Sources Data Systems Consumers

Enterprise Relational Data

CRM

ERP

Enterprise Reporting

Applications

Batch

Replication

Unstructured, Logs, Social

Self-ServiceExploration, Visualization

Batch

On-premises, in cloud, hybrid

Consolidated Diverse Data

Key Skills: Data Analysis, SQL, Modeling, Database Administration, ETL Development, Reporting, Visualization, Distributed Data Administration, Object-Oriented Programming

EDW

Big Data StoreHadoop: MapReduce

& HDFS, NoSQL, in Memory

~2010 - Big Data

3rd Party Data

Analytics

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~2015 - Advanced Analytics

Machine Learning, Predictive and Real-time Analytics, Automation

Key Skills: Data Analysis, SQL, Modeling, Database Administration, ETL Development, Reporting, Visualization, Distributed Data Administration, Object-Oriented Programming, A.I., Machine Learning, Deep Learning, Natural Language Processing, Automation.

Data Systems

EDW

Big Data Lake

Analytics Sandbox

Mach

ine

Learnin

g

Batch

Replication

ConsumersEnterprise Reporting

Batch

Ƒ ()

Self-ServiceExploration, Visualization

Predictive Modeling

StreamingReal-Time

Sources

Enterprise Relational Data

CRM

ERP

Unstructured, Social, Logs

3rd Party Data

Internet of Everything

Analytics

Applications

APIs

Automation

12

~2018+ - Interconnected Intelligent Enterprise

Distributed Interconnected Systems, Analytics Everywhere, Cloud

Data Systems Consumers

Enterprise Relational Data

CRM

ERP

Enterprise Reporting

Applications

Key Skills: Data Analysis, SQL, Modeling, Database Administration, ETL Development, Reporting, Visualization, Distributed Data Administration, Object-Oriented Programming, A.I., Machine Learning, Deep Learning, Natural Language Processing, Automation, Services, Cloud, Security

Batch

Replication

Unstructured, Social, Logs

3rd Party Data

Streaming

Batch

Data Fabric / Virtualization

EDW

Big Data Lake

Analytics Sandbox

Internet of Everything

On-premises, in cloud (public, private, hybrid)M

achin

e Learn

ing

APIs

Ƒ ()

Real-Time

Ƒ ()

Ƒ ()

Self-ServiceExploration, Visualization

Predictive Modeling

Ƒ ()

Analytics

Ƒ ()

Automation

Sources

Master Data Management

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DIGITAL INFORMATION CORECONCEPTUAL

DATA SOURCES

INGESTION AND

INTEGRATION

SECURE AND INTELLIGENT

DATA ACCESS

ANALYTICS-IN-MOTION

ADVANCED ANALYTICS SYSTEM

INFORMATION MANAGEMENT AND GOVERNANCE

ENHANCED APPLICATIONS

DISCOVERY ANDEXPLORATION

ACTIONABLEINSIGHTS

ANALYTICAL DATA STORAGE

CURATED DATA SETS

COMMON INTERFACES

TRUST EXPLORE RESEARCH

WHEN TO LEVERAGE THE DIGITAL INFORMATION CORE

INFORMED BY TRANSFORMATIVE BUSINESS OPPORTUNITIES

✓ Common taxonomy & metadata model for consistency

✓ Cognitive analysis & self-learning to deliver actionable insights

✓ Curate data by dynamically organizing & integrating a collection of data assets from internal & external sources

✓ Search, learn, & discover insights about disparate data sets with structured & unstructured content

INFORMATION-CENTRICBUSINESS VALUE DRIVEN

✓ Make business decisions, take action & achieve business outcomes

✓ Use relevant & trusted information to gain insight at the right time

✓ Improve efficiency, quality & accuracy by automatingrepeatable tasks & business processes

✓ Deliver personalized experiences to drive customer actions & behaviors

LINKING BUSINESS NEEDS TO INFORMATION OUTCOMES

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THANK YOU!

QUESTIONS?