big data vendor panel - data stax

Big Data in Healthcare

Amy McNee, VP Customer Engagement

05/05/2015

Technology landscape

LOB

App

Oracle

LOB

App

MySQL

LOB

App

SQL

Server

Data Warehouse

RDBMS

Teradata/Exadata

Column DB’s

LOB

App

NoSQL

LOB

App

NoSQL

LOB

App

NoSQL

C* C

*C*

C*C

*C*

C*

C*

C*

Data Warehouse

Hadoop

Traditional

Technology

NoSQL Technology

OLTP

(What’s Happening)OLAP

(What Happened)

C* C

*C*

C*C

*C*

C*

C*

C*

C* C

*C*

C*C

*C*

C*

C*

C*

DSE as a Platform for EHR

DC1 DC2 DC3

Standard Interfaces

Internode

Encryption

AD/LDAP

Kerberos

Driver to Node

Encryption

On Disk

Encryption

Search

Analytics

Application

Tools

• Always-On

• Fast Data Ingestion

• Enterprise Security

• Integrated Search &

Analytics

• Data Model

Flexibility

Se

cu

rity

Key Use Cases in Healthcare

• Consolidated Patient View

• Fraud Detection

• Analysis of Real-time physiological signals from data monitoring

devices

• Disease Identification

• Search and Taxonomy

© 2015 DataStax, All Rights Reserved. 4

Founded in April 2010

~500

Santa Clara, Austin, New York, London,

Paris, Tokyo, Melbourne

~400Employees Customers

~30Percent

Overview

We Deliver to Enterprise Software Standards

Support & Training

ProfessionalServices

Security

VisualMonitoring

ManagementServices

In-MemorySpark

Analytics

Search

Commercial

Confidence

Enterprise

Functionality

DSE

Certification

The New Connected World Needs

a Revolutionary New DBMS

“The Internet of Everything”

Client-Server

Static

SocialMobileCloud

Mainframe

1970’s

1990’s

Today

IBM

ORACLE

Semi-Connected Radically Connected

DATASTAX

Distributed

8

The Problem with Legacy Technology

Challenges

• Complexity

• Cost

• Performance

• Scalability

9

Powering Life Saving Recommendations with Real-time Analytics

Managing large volumes of dynamic structured and unstructured data

Need flexible data model capable of changing in real time

Search and analytics allow Amara Health Analytics to serve the recommendations to doctors

Spend less time administering the database and more time innovating to drive the business

Business critical applications require 24x7x365 expert support

Use Case: Recommendation/ Personalization

Nike Becomes a Technology Company with Nike+Nike+ will become the social network for all things activity related

Sensors track activities and performance against goal to create a better athlete

Scaling Nike+ system performance and regional access to data were key challenges

Failed to meet performance/availability targets with legacy RDBMS platform

Thorough evaluation of leading NoSQL technologies led to DSE being chosen as standard

Netflix – More Than Content

Highly optimized customer engagement

Over 1 Trillion transactions per day

Business agility made possible without infrastructure anchor

100% Amazon datacenters

Replaced Oracle in multiple regions across the worldUse Case: Personalization

11

Connected Homes Brings British Gas Closer to CustomersBritish Gas is the largest provider of domestic gas in the UK with 15M customers

Goal to move from “remote utility” to an “everyday companion in our customer’s lives”

Remote HVAC Control, Smart Energy Reports - live data from Smart Meters and Connected

Boilers

DataStax Enterprise with Spark Analytics chosen to handle large volumes of Time Series Data

Previous solution lacked Scalability, Performance and Management Capabilities

Delivers 150+ Billion Content Recommendations Per Month

Serves content for largest media brands in the world: Reuters, Wall St Journal, USA Today

Needed a massively scalable datastore

High velocity of data with 58,000 links to content per second

Always-on data architecture

Use Case: Recommendations / Personalization

Google Nest Revolutionizes the Thermostat

Google pays $3BN for Nest, not for thermostat, but for data

All interactions with customer thermostats are written to DataStax

All mobile application interactions are handled by DataStax

DataStax chosen for ability to handle high velocity writes in time series

Use Case: Internet Of Things14

Market Leadership Product Leadership Customer Leadership

Visionary in ODBMS

Leader

Market Leadership

Big Data Startups on the rise

Companies that matter most in data

Big Data 100: Data Management

Thank you!