SlideShare a Scribd company logo
Be Heroic
Analytics. For Anyone.
Turn Big Data
into Action
2
My journey….
Early Life
College
Early Career
Masters
Mid Career
3
About me now….
Michele Chambers
President/COO
@mcAnalytics
mchambers@rapidminer.com
4
Analytics on big data is no longer just a
competitive advantage.
It’s a Business
Requirement.
Progressive businesses must accelerate time-to-value not only to thrive, but survive.
5
Unlike traditional analytics providers,
RapidMiner enables anyone to make the
most of all data in all environments,
creating a powerful advantage from the
wisdom of over 250,000 users.
RapidMiner is the industry's easiest-to-use
Modern Analytics Platform that
significantly accelerates productivity – from
data blending to predictive action.
Built by data scientists for data scientists, businesses analysts, and developers.
6
TTraditional
MModern
Advanced Analytics Market Maturity
Lagging innovation
High-velocity innovation
7
TTraditional
Evolving Roles for Advanced Analytics
MModern
Status Quo
• Statisticians
• Quants
• Actuarials
Next Generation
• Data Scientists
• Business Analysts
8
TTraditional
Evolving Advanced Analytics Market
MModern
Limitations
• Limited handling of variety of data source
• Legacy compute engines
• On-premises, if not offline
Limitless
• Big Data
• New compute engines
• Cloud
9
Traditional vs. Modern Analytics Market
Magic Quadrant for
Advanced Analytics Platforms
February 2015
Challengers Leaders
Niche players Visionaries
Completeness of vision
Abilitytoexecute
Tibco Software
Prognoz
Salford Systems
Revolution Analytics
Predixion
Angoss
FICO
SAP
Dell
Microsoft
KNIME
IBM
SAS
RapidMiner
Alteryx
Alpine Data Labs
10
Enter RapidMiner. Analytics. For Anyone.
Accelerate
Pre-Built Templates
One-Click Deployments
Connect
All Data
All Environments
Simplify
Code-Free
Wisdom of Crowds
11
Wisdom of Crowds
How do we create data science heroes?
Store them in a
knowledge base
of analytic best practices
Anonymously collect
analytic processes
from analysts across the
enterprise
Use machine
learning algorithms
to recommend and
empower any user at any
skill level to become a
data science hero
1
2
3
12
Self Service Modern Analytics Platform
RapidMiner Studio
Code-free design your analytics
using 1500+ operators
RapidMiner Radoop
Push down computations to
where your data lives
RapidMiner Streams
Analyze streaming data while in
motion
RapidMiner Cloud
Elastic compute environment
for high performance analytics
RapidMiner Server
Enterprise analytics
environment for integration
with business processes
Orchestrate
Design
Compute
Business Analysts Data Scientists
Consume
Machine
Business Users
Web
App
Custom
App
Biz
App
VizBI
Studio
Code-Free GUI Engine
Engine
In-Memory In-DatabaseIn-Hadoop
Engine
Studio
Engine Engine
Streams
Engine
Radoop
Engine
Cloud
Engine
Server
Web Services API
In-Stream
Engine
13
IT
Use statistical tool to
•create ad hoc predictive
processes
Developer Data Scientists
Use programming
languages and libraries to:
•build completely new
algorithms
•create highly customized
advanced analytic processes
Applied Data Scientists
Use advanced analytic
platforms to:
•ingest and prepare data for
analysis
•identify patterns in data
•build and deploy novel
predictive apps
Business Analysts
Use advanced analytic
platforms to:
•ingest and prepare data
for analysis
•identify patterns in data
•build and deploy standard
predictive apps
Business Consumers
Use embedded predictive
results in frontline
applications
Maximize Analytic Skills Through Collaboration
Why RapidMiner:
Fast Production Deployments
Why RapidMiner:
Share Code Across Teams
Why RapidMiner:
Efficiency & Collaboration
Why RapidMiner:
Design Predictive Analytics
Why RapidMiner:
Actions in Front Line Apps
RapidMiner Studio
RapidMiner Radoop
RapidMiner Stream
RapidMiner Cloud
RapidMiner Server
14
RapidMiner Radoop Architecture
Hadoop environment
Impala
(In-memory SQL)
Mahout
(Machine
Learning)
Pig
(Scripting)
HDFS
YARNMapReduce
Hive
(SQL)
PROGRAMMING
CODE
VISUAL
DEVELOPMENT
Radoop
Studio Server
Spark
(MLib)
Ingestion Modeling DeploymentBlending
Code-free design
in RapidMiner
with 70+ Operators
Optimized distributed
execution in Hadoop
environment
One-click push down to
Hadoop environment
15
VISUAL
DEVELOPMENT
Streams
Studio Server
Apache Storm clusterMessage
broker
Apache
Kafka
Amazon
SQS
or
Application
Cassandra MongoDB
Apache
Kafka
Application
push pull
pull
store
deploy process
as topology
monitor and
manage
Redis
RapidMiner Streams Architecture Code-free design
in RapidMiner leveraging
1500+ Operators
Distributed execution in
Storm environment
One-click push down to
Storm environment
Node
Engine
Node
Node
Storm Topology
Node
Storm Topology
Node
Engine
Streams
Spout Bolt Bolt Bolt
Storm Topology
Bolt
Bolt
Ingestion Modeling DeploymentBlending
16
www.rapidminer.com
Activating the data science hero
in every business analyst!
Michele Chambers
@mcAnalytics
mchambers@rapidminer.com

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M Chambers and RapidMiner Overview for Babson class

  • 1. Be Heroic Analytics. For Anyone. Turn Big Data into Action
  • 2. 2 My journey…. Early Life College Early Career Masters Mid Career
  • 3. 3 About me now…. Michele Chambers President/COO @mcAnalytics mchambers@rapidminer.com
  • 4. 4 Analytics on big data is no longer just a competitive advantage. It’s a Business Requirement. Progressive businesses must accelerate time-to-value not only to thrive, but survive.
  • 5. 5 Unlike traditional analytics providers, RapidMiner enables anyone to make the most of all data in all environments, creating a powerful advantage from the wisdom of over 250,000 users. RapidMiner is the industry's easiest-to-use Modern Analytics Platform that significantly accelerates productivity – from data blending to predictive action. Built by data scientists for data scientists, businesses analysts, and developers.
  • 6. 6 TTraditional MModern Advanced Analytics Market Maturity Lagging innovation High-velocity innovation
  • 7. 7 TTraditional Evolving Roles for Advanced Analytics MModern Status Quo • Statisticians • Quants • Actuarials Next Generation • Data Scientists • Business Analysts
  • 8. 8 TTraditional Evolving Advanced Analytics Market MModern Limitations • Limited handling of variety of data source • Legacy compute engines • On-premises, if not offline Limitless • Big Data • New compute engines • Cloud
  • 9. 9 Traditional vs. Modern Analytics Market Magic Quadrant for Advanced Analytics Platforms February 2015 Challengers Leaders Niche players Visionaries Completeness of vision Abilitytoexecute Tibco Software Prognoz Salford Systems Revolution Analytics Predixion Angoss FICO SAP Dell Microsoft KNIME IBM SAS RapidMiner Alteryx Alpine Data Labs
  • 10. 10 Enter RapidMiner. Analytics. For Anyone. Accelerate Pre-Built Templates One-Click Deployments Connect All Data All Environments Simplify Code-Free Wisdom of Crowds
  • 11. 11 Wisdom of Crowds How do we create data science heroes? Store them in a knowledge base of analytic best practices Anonymously collect analytic processes from analysts across the enterprise Use machine learning algorithms to recommend and empower any user at any skill level to become a data science hero 1 2 3
  • 12. 12 Self Service Modern Analytics Platform RapidMiner Studio Code-free design your analytics using 1500+ operators RapidMiner Radoop Push down computations to where your data lives RapidMiner Streams Analyze streaming data while in motion RapidMiner Cloud Elastic compute environment for high performance analytics RapidMiner Server Enterprise analytics environment for integration with business processes Orchestrate Design Compute Business Analysts Data Scientists Consume Machine Business Users Web App Custom App Biz App VizBI Studio Code-Free GUI Engine Engine In-Memory In-DatabaseIn-Hadoop Engine Studio Engine Engine Streams Engine Radoop Engine Cloud Engine Server Web Services API In-Stream Engine
  • 13. 13 IT Use statistical tool to •create ad hoc predictive processes Developer Data Scientists Use programming languages and libraries to: •build completely new algorithms •create highly customized advanced analytic processes Applied Data Scientists Use advanced analytic platforms to: •ingest and prepare data for analysis •identify patterns in data •build and deploy novel predictive apps Business Analysts Use advanced analytic platforms to: •ingest and prepare data for analysis •identify patterns in data •build and deploy standard predictive apps Business Consumers Use embedded predictive results in frontline applications Maximize Analytic Skills Through Collaboration Why RapidMiner: Fast Production Deployments Why RapidMiner: Share Code Across Teams Why RapidMiner: Efficiency & Collaboration Why RapidMiner: Design Predictive Analytics Why RapidMiner: Actions in Front Line Apps RapidMiner Studio RapidMiner Radoop RapidMiner Stream RapidMiner Cloud RapidMiner Server
  • 14. 14 RapidMiner Radoop Architecture Hadoop environment Impala (In-memory SQL) Mahout (Machine Learning) Pig (Scripting) HDFS YARNMapReduce Hive (SQL) PROGRAMMING CODE VISUAL DEVELOPMENT Radoop Studio Server Spark (MLib) Ingestion Modeling DeploymentBlending Code-free design in RapidMiner with 70+ Operators Optimized distributed execution in Hadoop environment One-click push down to Hadoop environment
  • 15. 15 VISUAL DEVELOPMENT Streams Studio Server Apache Storm clusterMessage broker Apache Kafka Amazon SQS or Application Cassandra MongoDB Apache Kafka Application push pull pull store deploy process as topology monitor and manage Redis RapidMiner Streams Architecture Code-free design in RapidMiner leveraging 1500+ Operators Distributed execution in Storm environment One-click push down to Storm environment Node Engine Node Node Storm Topology Node Storm Topology Node Engine Streams Spout Bolt Bolt Bolt Storm Topology Bolt Bolt Ingestion Modeling DeploymentBlending
  • 16. 16 www.rapidminer.com Activating the data science hero in every business analyst! Michele Chambers @mcAnalytics mchambers@rapidminer.com

Editor's Notes

  1. Secondary SkyTree Knime Pentaho Alpine Data Miner Datameer Google API RM 5.3 ? Amazon KXEN / SAP
  2. Secondary SkyTree Knime Pentaho Alpine Data Miner Datameer Google API RM 5.3 ? Amazon KXEN / SAP
  3. Secondary SkyTree Knime Pentaho Alpine Data Miner Datameer Google API RM 5.3 ? Amazon KXEN / SAP