SlideShare a Scribd company logo
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
LOWERING THE ENTRY POINT TO GETTING GOING
WITH HADOOP AND OBTAINING BUSINESS VALUE
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
SAS & HADOOP WHO IS SAS?
• Almost 4 decades of Advanced Analytics & DM expertise.
• Validated by Gartner and Forrester Analysts as Leaders in
Advanced Analytics, BI and DM.
• Leader in *17* Gartner’s Magic Quadrants from Data
Management, BI to Advanced Analytics.
• 400 offices, 70,000+ customers, 135 countries with largest
ecosystem of users and partners.
• 38% of Advanced Analytics Market Share (per IDC).
• 25% reinvested into R&D.
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
GARTNER: MAGIC QUADRANT FOR ADVANCED ANALYTIC PLATFORMS
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from SAS. Gartner does not endorse any vendor, product or
service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and
should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.
Gartner Magic Quadrant for Advanced Analytics Platforms by Gareth Herschel, Alexander Linden, Lisa Kart, 19 February 2015.
Gartner defines advanced
analytics as, "the analysis of all
kinds of data using
sophisticated quantitative
methods (for example,
statistics, descriptive and
predictive data mining,
simulation and optimization) to
produce insights that traditional
approaches to business
intelligence (BI) — such as
query and reporting — are
unlikely to discover."
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
SAS & INTEL
STUDY
HADOOP ADOPTION & CHALLENGES
Research summary: SAS and Intel asked more
than 300 IT-managers from the largest companies
in Denmark, Finland, Norway and Sweden about
the adoption of Big Data analytics and Hadoop.
http://nordichadoopsurvey.com
60% - cited advanced analytics,
data discovery, or as an
analytical lab
22% - would like to
speed up processing
Primary reason for considering Hadoop
Adoption / Obstacles
35% - cited “Resources and Competencies”
Results & Key
Findings
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
CHALLENGE HADOOP SKILLS SHORTAGE
Performing even the simplest tasks in
Hadoop typically requires mastering
disparate tools and writing hundreds of
lines of code.
Fact: There are a limited # of users
with the necessary Hadoop skills
• MapReduce
• Pig Latin
• HiveQL
• HDFS
• Sqoop and Oozie
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
CHALLENGE USER TOOLS ARE NOT BIG DATA ENABLED
Big data brings new requirements:
• Access to HDFS
• Parallel Loads
• New Native file types
• Knowledge of file structures
• New languages & code
• Need to transform data In-cluster
User tools are not engineered to process
data inside Hadoop.
• Tools are not optimized for Hadoop
• Users move data out of Hadoop to do
data management and data quality
• This requires more processing time
• Data is duplicated and more storage is
required
• Users do not use the Hadoop platform
as it was designed
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
BIG DATA
MANAGEMENT
ANALYSTS TAKE
Recommendation
“Use self-service interactive data preparation
tools to enhance analyst productivity.” and
“improve the quality of data”
– Gartner, “Data Preparation Is Not an Afterthought”
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
SAS & HADOOP HOW?
SAS & Hadoop intersect in many ways:
 SAS can treat Hadoop just as any other data source, pulling data
FROM Hadoop, when it is most convenient;
 SAS can work WITH Hadoop, lifting data in a purpose-built
advanced analytics in-memory environment;
 SAS can work directly IN Hadoop, leveraging the distributed
processing capabilities of Hadoop.



Copyright © 2015, SAS Institute Inc. All rights reserv ed.
SAS & HADOOP THE PRAGMATIC APPROACH
Prepare data IN
Hadoop for analytics
Move data FROM
Hadoop into a SAS
environment
Deploy and manage
model score code IN
Hadoop
Lift data IN to memory
for analytics
Model data in-memory
WITH advanced
modeling tools
Use the
right
approach for
what needs
to be done!
Explore data in-memory
WITH data
visualization and
approachable
modelling
MANAGE
DATA
EXPLORE
DATA
DEVELOP
MODELS
DEPLOY&
MONITOR
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
DEMO
• Sector: Online e-commerce shop
• Business Problem: Having difficulty to keep
profitable customers returning to the web site
• Specific aim: Identify the reasons for clients to
abandon their shopping cart and predict those
visitors with a high probability to abandon
• Challenge: Getting big data stored into Hadoop
and accessing it is difficult for analysts to access
from their traditional systems without specific
expertise
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
ENABLING ENTIRE ANALYTICS LIFECYCLE AROUND HADOOP
TEXT
MANAGE
DATA
EXPLORE
DATA
DEVELOP
MODELS
DEPLOY&
MONITOR
• SAS/ACCESS to Hadoop
• SAS Data Loader for Hadoop
• SAS Data Management
• SAS Federation Server
• SAS Event Stream Processing
• SAS Visual Analytics
• SAS In-memory Statistics
• SAS Visual Statistics
• SAS High-Performance
Analytics Products
• SAS Scoring Accelerator for
Hadoop
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
WHY SAS?
SUPPORTING THE ENTIRE
ANALYTICS JOURNEY!
SAS® Visual Analytics
SAS® Visual Statistics
SAS® In-Memory
Statistics
SAS® Enterprise Miner /
SAS® Forecast Server
SAS® Decision Manager /
SAS® Scoring Accelerator
Data exploration,
analysis,
visualization and
approachable
analytics for the
masses
In-depth GUI driven
approachable
modelling
State-of-the-art
interactive
analytics driven
through a
programmatic
interface
Robust production
modelling tools that
provide for
repeatability and
easy
operationalization
Capabilities to
deploy, monitor and
automate analytics
with appropriate
business rules into
operational business
processes
Visualize, explore, interact, explain, understand, democratize
Finalize, Deploy, integrate, execute,
operationalize, industrialize
SAS® Data Loader for Hadoop
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
SAS AND HADOOP SUMMARY
 SAS is the only vendor to work FROM + WITH + IN Hadoop throughout
the analytics lifecycle.
 All three approaches can be combined and coordinated,
complementing each other for each situation.
 Each approach can evolve, mature and/or morph into the other.
 SAS can help realize the value of Hadoop; bring production-analytics to
the platform.
Copyright © 2015, SAS Institute Inc. All rights reserv ed.
THANK YOU
MARK.TORR@SAS.COM
Lets connect on LinkedIn: http://de.linkedin.com/in/marktorr/en
Follow my interests on Twitter: https://twitter.com/mark_torr

More Related Content

PDF
"Integration of Hadoop in Business landscape", Michal Alexa, IT and Innovatio...
PPTX
Netezza integration with SAS software
PPTX
SAS Modernization architectures - Big Data Analytics
PDF
SAS and Netezza Enzee universe presentation_20_june2011
PPTX
Sas visual analytics training presentation
PDF
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
PPTX
Ambari Meetup: 2nd April 2013: Teradata Viewpoint Hadoop Integration with Ambari
PPTX
SAS and Cloudera – Analytics at Scale
"Integration of Hadoop in Business landscape", Michal Alexa, IT and Innovatio...
Netezza integration with SAS software
SAS Modernization architectures - Big Data Analytics
SAS and Netezza Enzee universe presentation_20_june2011
Sas visual analytics training presentation
Big Data Integration Webinar: Reducing Implementation Efforts of Hadoop, NoSQ...
Ambari Meetup: 2nd April 2013: Teradata Viewpoint Hadoop Integration with Ambari
SAS and Cloudera – Analytics at Scale

What's hot (20)

PDF
The Value of the Modern Data Architecture with Apache Hadoop and Teradata
PDF
How to get started in Big Data without Big Costs - StampedeCon 2016
PPTX
Swimming Across the Data Lake, Lessons learned and keys to success
PPTX
Data Discovery & Lineage in Enterprise Hadoop
PPTX
Hybrid Data Architecture: Integrating Hadoop with a Data Warehouse
PPTX
10 Amazing Things To Do With a Hadoop-Based Data Lake
PPTX
How to build a successful Data Lake
PDF
Alexandre Vasseur - Evolution of Data Architectures: From Hadoop to Data Lake...
PPTX
Pentaho big data camp - 5 min
PPTX
Bay Area Hadoop User Group
PDF
Big Data Discovery
PDF
Beyond Big Data: Data Science and AI
PPTX
Operational Analytics Using Spark and NoSQL Data Stores
PDF
Big data/Hadoop/HANA Basics
PDF
Data Management for High Performance Analytics
PDF
Turn Data Into Actionable Insights - StampedeCon 2016
PPTX
Hadoop in Validated Environment - Data Governance Initiative
PPTX
Deploying a Governed Data Lake
PPTX
Hortonworks Oracle Big Data Integration
PPTX
Partners 2013 LinkedIn Use Cases for Teradata Connectors for Hadoop
The Value of the Modern Data Architecture with Apache Hadoop and Teradata
How to get started in Big Data without Big Costs - StampedeCon 2016
Swimming Across the Data Lake, Lessons learned and keys to success
Data Discovery & Lineage in Enterprise Hadoop
Hybrid Data Architecture: Integrating Hadoop with a Data Warehouse
10 Amazing Things To Do With a Hadoop-Based Data Lake
How to build a successful Data Lake
Alexandre Vasseur - Evolution of Data Architectures: From Hadoop to Data Lake...
Pentaho big data camp - 5 min
Bay Area Hadoop User Group
Big Data Discovery
Beyond Big Data: Data Science and AI
Operational Analytics Using Spark and NoSQL Data Stores
Big data/Hadoop/HANA Basics
Data Management for High Performance Analytics
Turn Data Into Actionable Insights - StampedeCon 2016
Hadoop in Validated Environment - Data Governance Initiative
Deploying a Governed Data Lake
Hortonworks Oracle Big Data Integration
Partners 2013 LinkedIn Use Cases for Teradata Connectors for Hadoop
Ad

Similar to Lowering the entry point to getting going with Hadoop and obtaining business value (20)

PPTX
Accelerate Your Big Data Analytics Efforts with SAS and Hadoop
PPTX
Tableau and hadoop
PPTX
Hadoop Reporting and Analysis - Jaspersoft
PPTX
2015 HortonWorks MDA Roadshow Presentation
PDF
How Can I Save Time and Build Trust With My Data Preparation.pdf
PDF
SAS Data Management for Analytics: potenzia le tue analisi e sostieni l’innov...
PDF
Exclusive Verizon Employee Webinar: Getting More From Your CDR Data
PPTX
Business Visualization: Dashboard & Storyboarding
PDF
What's New with SAP BusinessObjects Business Intelligence 4.1?
PDF
Leveraging SAP HANA with Apache Hadoop and SAP Analytics
PPTX
Big Data for BI - Beyond the Hype - Pentaho
PDF
SAS Visual Analytics
PDF
Contexti / Oracle - Big Data : From Pilot to Production
PDF
BAR360 open data platform presentation at DAMA, Sydney
PDF
Data & Analytics with CIS & Microsoft Platforms
PDF
Eliminating the Challenges of Big Data Management Inside Hadoop
PDF
Eliminating the Challenges of Big Data Management Inside Hadoop
PPTX
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
PDF
Ramesh kutumbaka resume
PDF
Hadoop and the Data Warehouse: When to Use Which
Accelerate Your Big Data Analytics Efforts with SAS and Hadoop
Tableau and hadoop
Hadoop Reporting and Analysis - Jaspersoft
2015 HortonWorks MDA Roadshow Presentation
How Can I Save Time and Build Trust With My Data Preparation.pdf
SAS Data Management for Analytics: potenzia le tue analisi e sostieni l’innov...
Exclusive Verizon Employee Webinar: Getting More From Your CDR Data
Business Visualization: Dashboard & Storyboarding
What's New with SAP BusinessObjects Business Intelligence 4.1?
Leveraging SAP HANA with Apache Hadoop and SAP Analytics
Big Data for BI - Beyond the Hype - Pentaho
SAS Visual Analytics
Contexti / Oracle - Big Data : From Pilot to Production
BAR360 open data platform presentation at DAMA, Sydney
Data & Analytics with CIS & Microsoft Platforms
Eliminating the Challenges of Big Data Management Inside Hadoop
Eliminating the Challenges of Big Data Management Inside Hadoop
Modernizing Business Processes with Big Data: Real-World Use Cases for Produc...
Ramesh kutumbaka resume
Hadoop and the Data Warehouse: When to Use Which
Ad

More from DataWorks Summit (20)

PPTX
Data Science Crash Course
PPTX
Floating on a RAFT: HBase Durability with Apache Ratis
PPTX
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
PDF
HBase Tales From the Trenches - Short stories about most common HBase operati...
PPTX
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
PPTX
Managing the Dewey Decimal System
PPTX
Practical NoSQL: Accumulo's dirlist Example
PPTX
HBase Global Indexing to support large-scale data ingestion at Uber
PPTX
Scaling Cloud-Scale Translytics Workloads with Omid and Phoenix
PPTX
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFi
PPTX
Supporting Apache HBase : Troubleshooting and Supportability Improvements
PPTX
Security Framework for Multitenant Architecture
PDF
Presto: Optimizing Performance of SQL-on-Anything Engine
PPTX
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
PPTX
Extending Twitter's Data Platform to Google Cloud
PPTX
Event-Driven Messaging and Actions using Apache Flink and Apache NiFi
PPTX
Securing Data in Hybrid on-premise and Cloud Environments using Apache Ranger
PPTX
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
PDF
Computer Vision: Coming to a Store Near You
PPTX
Big Data Genomics: Clustering Billions of DNA Sequences with Apache Spark
Data Science Crash Course
Floating on a RAFT: HBase Durability with Apache Ratis
Tracking Crime as It Occurs with Apache Phoenix, Apache HBase and Apache NiFi
HBase Tales From the Trenches - Short stories about most common HBase operati...
Optimizing Geospatial Operations with Server-side Programming in HBase and Ac...
Managing the Dewey Decimal System
Practical NoSQL: Accumulo's dirlist Example
HBase Global Indexing to support large-scale data ingestion at Uber
Scaling Cloud-Scale Translytics Workloads with Omid and Phoenix
Building the High Speed Cybersecurity Data Pipeline Using Apache NiFi
Supporting Apache HBase : Troubleshooting and Supportability Improvements
Security Framework for Multitenant Architecture
Presto: Optimizing Performance of SQL-on-Anything Engine
Introducing MlFlow: An Open Source Platform for the Machine Learning Lifecycl...
Extending Twitter's Data Platform to Google Cloud
Event-Driven Messaging and Actions using Apache Flink and Apache NiFi
Securing Data in Hybrid on-premise and Cloud Environments using Apache Ranger
Big Data Meets NVM: Accelerating Big Data Processing with Non-Volatile Memory...
Computer Vision: Coming to a Store Near You
Big Data Genomics: Clustering Billions of DNA Sequences with Apache Spark

Recently uploaded (20)

PDF
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
PDF
Encapsulation theory and applications.pdf
PDF
Diabetes mellitus diagnosis method based random forest with bat algorithm
PDF
Dropbox Q2 2025 Financial Results & Investor Presentation
PPTX
Understanding_Digital_Forensics_Presentation.pptx
PPTX
Cloud computing and distributed systems.
PPTX
20250228 LYD VKU AI Blended-Learning.pptx
PPTX
A Presentation on Artificial Intelligence
PDF
Spectral efficient network and resource selection model in 5G networks
PDF
Advanced methodologies resolving dimensionality complications for autism neur...
PDF
KodekX | Application Modernization Development
PDF
Blue Purple Modern Animated Computer Science Presentation.pdf.pdf
PPT
“AI and Expert System Decision Support & Business Intelligence Systems”
PPTX
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
PPTX
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
PDF
CIFDAQ's Market Insight: SEC Turns Pro Crypto
PDF
Electronic commerce courselecture one. Pdf
PDF
Shreyas Phanse Resume: Experienced Backend Engineer | Java • Spring Boot • Ka...
PDF
The Rise and Fall of 3GPP – Time for a Sabbatical?
PDF
Bridging biosciences and deep learning for revolutionary discoveries: a compr...
7 ChatGPT Prompts to Help You Define Your Ideal Customer Profile.pdf
Encapsulation theory and applications.pdf
Diabetes mellitus diagnosis method based random forest with bat algorithm
Dropbox Q2 2025 Financial Results & Investor Presentation
Understanding_Digital_Forensics_Presentation.pptx
Cloud computing and distributed systems.
20250228 LYD VKU AI Blended-Learning.pptx
A Presentation on Artificial Intelligence
Spectral efficient network and resource selection model in 5G networks
Advanced methodologies resolving dimensionality complications for autism neur...
KodekX | Application Modernization Development
Blue Purple Modern Animated Computer Science Presentation.pdf.pdf
“AI and Expert System Decision Support & Business Intelligence Systems”
VMware vSphere Foundation How to Sell Presentation-Ver1.4-2-14-2024.pptx
Detection-First SIEM: Rule Types, Dashboards, and Threat-Informed Strategy
CIFDAQ's Market Insight: SEC Turns Pro Crypto
Electronic commerce courselecture one. Pdf
Shreyas Phanse Resume: Experienced Backend Engineer | Java • Spring Boot • Ka...
The Rise and Fall of 3GPP – Time for a Sabbatical?
Bridging biosciences and deep learning for revolutionary discoveries: a compr...

Lowering the entry point to getting going with Hadoop and obtaining business value

  • 1. Copyright © 2015, SAS Institute Inc. All rights reserv ed. LOWERING THE ENTRY POINT TO GETTING GOING WITH HADOOP AND OBTAINING BUSINESS VALUE
  • 2. Copyright © 2015, SAS Institute Inc. All rights reserv ed. SAS & HADOOP WHO IS SAS? • Almost 4 decades of Advanced Analytics & DM expertise. • Validated by Gartner and Forrester Analysts as Leaders in Advanced Analytics, BI and DM. • Leader in *17* Gartner’s Magic Quadrants from Data Management, BI to Advanced Analytics. • 400 offices, 70,000+ customers, 135 countries with largest ecosystem of users and partners. • 38% of Advanced Analytics Market Share (per IDC). • 25% reinvested into R&D.
  • 3. Copyright © 2015, SAS Institute Inc. All rights reserv ed. GARTNER: MAGIC QUADRANT FOR ADVANCED ANALYTIC PLATFORMS This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from SAS. Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner's research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose. Gartner Magic Quadrant for Advanced Analytics Platforms by Gareth Herschel, Alexander Linden, Lisa Kart, 19 February 2015. Gartner defines advanced analytics as, "the analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover."
  • 4. Copyright © 2015, SAS Institute Inc. All rights reserv ed. SAS & INTEL STUDY HADOOP ADOPTION & CHALLENGES Research summary: SAS and Intel asked more than 300 IT-managers from the largest companies in Denmark, Finland, Norway and Sweden about the adoption of Big Data analytics and Hadoop. http://nordichadoopsurvey.com 60% - cited advanced analytics, data discovery, or as an analytical lab 22% - would like to speed up processing Primary reason for considering Hadoop Adoption / Obstacles 35% - cited “Resources and Competencies” Results & Key Findings
  • 5. Copyright © 2015, SAS Institute Inc. All rights reserv ed. CHALLENGE HADOOP SKILLS SHORTAGE Performing even the simplest tasks in Hadoop typically requires mastering disparate tools and writing hundreds of lines of code. Fact: There are a limited # of users with the necessary Hadoop skills • MapReduce • Pig Latin • HiveQL • HDFS • Sqoop and Oozie
  • 6. Copyright © 2015, SAS Institute Inc. All rights reserv ed. CHALLENGE USER TOOLS ARE NOT BIG DATA ENABLED Big data brings new requirements: • Access to HDFS • Parallel Loads • New Native file types • Knowledge of file structures • New languages & code • Need to transform data In-cluster User tools are not engineered to process data inside Hadoop. • Tools are not optimized for Hadoop • Users move data out of Hadoop to do data management and data quality • This requires more processing time • Data is duplicated and more storage is required • Users do not use the Hadoop platform as it was designed
  • 7. Copyright © 2015, SAS Institute Inc. All rights reserv ed. BIG DATA MANAGEMENT ANALYSTS TAKE Recommendation “Use self-service interactive data preparation tools to enhance analyst productivity.” and “improve the quality of data” – Gartner, “Data Preparation Is Not an Afterthought”
  • 8. Copyright © 2015, SAS Institute Inc. All rights reserv ed. SAS & HADOOP HOW? SAS & Hadoop intersect in many ways:  SAS can treat Hadoop just as any other data source, pulling data FROM Hadoop, when it is most convenient;  SAS can work WITH Hadoop, lifting data in a purpose-built advanced analytics in-memory environment;  SAS can work directly IN Hadoop, leveraging the distributed processing capabilities of Hadoop.   
  • 9. Copyright © 2015, SAS Institute Inc. All rights reserv ed. SAS & HADOOP THE PRAGMATIC APPROACH Prepare data IN Hadoop for analytics Move data FROM Hadoop into a SAS environment Deploy and manage model score code IN Hadoop Lift data IN to memory for analytics Model data in-memory WITH advanced modeling tools Use the right approach for what needs to be done! Explore data in-memory WITH data visualization and approachable modelling MANAGE DATA EXPLORE DATA DEVELOP MODELS DEPLOY& MONITOR
  • 10. Copyright © 2015, SAS Institute Inc. All rights reserv ed. DEMO • Sector: Online e-commerce shop • Business Problem: Having difficulty to keep profitable customers returning to the web site • Specific aim: Identify the reasons for clients to abandon their shopping cart and predict those visitors with a high probability to abandon • Challenge: Getting big data stored into Hadoop and accessing it is difficult for analysts to access from their traditional systems without specific expertise
  • 11. Copyright © 2015, SAS Institute Inc. All rights reserv ed. ENABLING ENTIRE ANALYTICS LIFECYCLE AROUND HADOOP TEXT MANAGE DATA EXPLORE DATA DEVELOP MODELS DEPLOY& MONITOR • SAS/ACCESS to Hadoop • SAS Data Loader for Hadoop • SAS Data Management • SAS Federation Server • SAS Event Stream Processing • SAS Visual Analytics • SAS In-memory Statistics • SAS Visual Statistics • SAS High-Performance Analytics Products • SAS Scoring Accelerator for Hadoop
  • 12. Copyright © 2015, SAS Institute Inc. All rights reserv ed. WHY SAS? SUPPORTING THE ENTIRE ANALYTICS JOURNEY! SAS® Visual Analytics SAS® Visual Statistics SAS® In-Memory Statistics SAS® Enterprise Miner / SAS® Forecast Server SAS® Decision Manager / SAS® Scoring Accelerator Data exploration, analysis, visualization and approachable analytics for the masses In-depth GUI driven approachable modelling State-of-the-art interactive analytics driven through a programmatic interface Robust production modelling tools that provide for repeatability and easy operationalization Capabilities to deploy, monitor and automate analytics with appropriate business rules into operational business processes Visualize, explore, interact, explain, understand, democratize Finalize, Deploy, integrate, execute, operationalize, industrialize SAS® Data Loader for Hadoop
  • 13. Copyright © 2015, SAS Institute Inc. All rights reserv ed. SAS AND HADOOP SUMMARY  SAS is the only vendor to work FROM + WITH + IN Hadoop throughout the analytics lifecycle.  All three approaches can be combined and coordinated, complementing each other for each situation.  Each approach can evolve, mature and/or morph into the other.  SAS can help realize the value of Hadoop; bring production-analytics to the platform.
  • 14. Copyright © 2015, SAS Institute Inc. All rights reserv ed. THANK YOU MARK.TORR@SAS.COM Lets connect on LinkedIn: http://de.linkedin.com/in/marktorr/en Follow my interests on Twitter: https://twitter.com/mark_torr