powering the "as it happens" business
TRANSCRIPT
© 2015 MapR Technologies 2
MapR: Best Solution for Customer Success
Premier
InvestorsHigh Growth
2X Growth In Direct Customers
90%Subscription Licenses
Software Margins
140% Dollar-based Net Expansion
700+ Customers
2X Growth In Annual
Subscriptions ( ACV)
Best Product
Apache Open Source
© 2015 MapR Technologies 3
CIO “Must Have” Strategies Over Time
Distributed
Computing?Big
Data?
Web?
Ecommerce?
Cloud?
Social?
Mobile?
Open
Source?
© 2015 MapR Technologies 4
CIO “Must Have” Strategies Over Time
Distributed
Computing?Big
Data?
Web?
Ecommerce?
Cloud?
Social?
Mobile?
Open
Source?
Back Office
“Automation”
“Cost reduction”
“Retrospective”
Front Office
“Customer intimacy”
“Revenue creation”
“Just-in-time”
© 2015 MapR Technologies 5
Advantage From Speeding Data-to-Action Cycle
The “As it Happens” Business
What
happened
historically?
What can we
do to affect
change?
What’s
happening
now?
© 2015 MapR Technologies 6
MapR Vision
Empowering the
“As-it-Happens” business
by speeding up the
data-to-action cycle
© 2015 MapR Technologies 7
MapR Architected A Platform For The Age Of Big Data
Apps
Databases
Operational
App platform
Storage
1980s 2000s 2010s
Big data apps
RDBMs
SAN/NAS
Monolithic
UNIX Linux
RDBMs
Scale out
Web
Structured Unstructured
Operational Analytics
© 2015 MapR Technologies 8
Alternatives Do Big OR Fast, But Not Both
BigLimited reliability
Limited functionality
Batch (mostly)
Rewrite Existing Apps
Fast
Expensive
Special purpose
Coding required for speed
Limited scale
Limited functionality
OR
© 2015 MapR Technologies 9
Multiple Workloads Today
Hadoop Batch
Import/
Export
Any
Operational
DBMS
Customer
360° Dashboard
Churn Analysis
(predictive
analysis)
DB
Operations
Web
Application
Server
Mobile
Application
Server
Data
Exploration
(SQL)
This is how most clients solve Big and Fast
© 2015 MapR Technologies 10
For the ”As-it-Happens” business: It Must Be Both Big And Fast
Unlimited Scale
Data diversity
Evolving schemas
Affordable
Secure
Reliable
Manageable
Fast ingestion
Batch & streaming
Polyglot
RDBMS & NoSQL
General purpose
Affordable
Big FastAND
© 2015 MapR Technologies 11
Integrated
Real Time
and Actionable
Analytics
Real-time
Ad Targeting
Product/sService
Optimization and
Personalization
• Single cluster
• Real time
• High performance, low latency
• Large-scale analytics
• Enterprise-grade HA/DR
• Unified file and table administration
Customer
360° Dashboard
Churn Analysis
(predictive
analysis)
DB
Operations
Web
Application
Server
Mobile
Application
Server
Data
Exploration
(SQL)
One Integrated System For Big & Fast
© 2015 MapR Technologies 13
Other Hadoop Distributions Have Limitations
APACHE HADOOP AND OSS ECOSYSTEM
Security
YARN
Spark Streaming
Storm
StreamingNoSQL & Search
Juju
Provisioning &
coordination
Savannah
ML, Graph
Mahout
MLLib
GraphX
EXECUTION ENGINES DATA GOVERNANCE AND OPERATIONS
Workflow & Data
Governance
Pig
Cascading
Spark
Batch
MapReduce v1 & v2
Tez
HBase
Solr
Hive
Impala
Spark SQL
Drill
SQL
Sentry Oozie ZooKeeperSqoop
Flume
Data Integration& Access
HttpFS
Hue
MapR Data Platform(Random Read/Write)
Can’t scaleNo update in-place
or handling streamsSingle points of
failure. No data center-class
reliability
Batch only. Need separate
systems
for real time
HDFS can only be a platform for
Hadoop and nothing else
© 2015 MapR Technologies 14
MapR: The Only Platform Architected For Big, Fast, Reliable
APACHE HADOOP AND OSS ECOSYSTEM
Security
YARN
Spark Streaming
Storm
StreamingNoSQL & Search
Juju
Provisioning &
coordination
Savannah
ML, Graph
Mahout
MLLib
GraphX
EXECUTION ENGINES DATA GOVERNANCE AND OPERATIONS
Workflow & Data
Governance
Pig
Cascading
Spark
Batch
MapReduce v1 & v2
Tez
HBase
Solr
Hive
Impala
Spark SQL
Drill
SQL
Sentry Oozie ZooKeeperSqoop
Flume
Data Integration& Access
HttpFS
Hue
MapR Data Platform(Random Read/Write)
MapR-FSHDFS and NFS APIs
MapR-DB(High-Performance NoSQL)
More efficient use of
infrastructure
First new
database
designed
for
operational
real-time
Surf any data
easily
Industry’s only mirroring, point-
in-time consistent snapshots
Trillion filesUnique
Unique
Unique
Unique
Unique
2-7x faster
Open source
Projects ‘inherit’
MapR’s platform
attributes
© 2015 MapR Technologies 15
Real-Time Hadoop Requirements
REAL-TIME DATA
REAL-TIME APPLICATIONS
REAL-TIME ANALYTICS
© 2015 MapR Technologies 18
"Our customers were saying, 'Look, I have chosen Teradata as
best-in-class data warehousing; I have chosen MapR as best-
in-class Hadoop infrastructure. I want you guys to integrate those together,'" said Teradata Vice President of Product and Services Marketing Chris Twogood. "Amongst our customers,
90 percent of them were saying we want tighter integration.“
MapR Hadoop Gets Blessing From Data Warehouse Giant
Teradata
CRN, Nov 19, 2014
© 2015 MapR Technologies 19
Partnership Announced on November 19th, 2014
• Teradata’s UDA one-stop-shop strategy is now extended to MapR
– Teradata customers get single vendor accountable for the full Hadoop ecosystem
– Teradata now a strategic partner to design, implement & provide solutions with MapR
• Deeper software integration between Teradata and MapR
– Seamless access across the Teradata UDA
– Teradata QueryGrid to support MapR
– Teradata Loom fully supports MapR Distribution for Hadoop
• Resell of subscriptions (license + support) for 3 core MapR products
– MapR Community Edition (free version, Teradata Customer Support)
– MapR Enterprise Edition (license and Teradata Customer Support)
– MapR Enterprise Database Edition (license and Teradata Customer Support)
• Teradata can resell Professional Services and Training curriculum
– Teradata can sell MapR education and training services and professional services to Teradata customers
– Through one phone call, provides single vendor accountability across the UDA
MapR & Teradata Expand PartnershipPartnership extends Hadoop choices by providing integration,
joint product development, and unified go-to-market strategy
© 2015 MapR Technologies 20
• Economically Capture and Store More Data
• Analytics on Low Business Value Density Data
• Enterprise-grade NoSQL Database
• Economically
Reuse and Share
Data
• Analytics on High
Business Value
Density Data
• EDW Leader
Right Tool for the Right Job
Teradata and MapR – Architecture Matters
© 2015 MapR Technologies 21
Marketing
Executives
Operational
Systems
Frontline
Workers
Customers
Partners
Engineers
Data
Scientists
Business
Analysts'
Math
and Stats
Data
Mining
Business
Intelligence
Applications
Languages
Marketing
APPLICATIONS
USERS
DISCOVERY PLATFORM
INTEGRATED DATA WAREHOUSE
ERP
SCM
CRM
Images
Audio
and Video
Machine
Logs
Text
Web and
Social
SOURCES
DATAPLATFORM
TERADATA UNIFIED DATA ARCHITECTURE
ACCESSMOVEMANAGE
STREAMING &NOSQL APP’SSTREAMING &NOSQL APP’S
© 2015 MapR Technologies 22
Capability Community Edition Enterprise EditionEnterprise Database
Edition
MapR Distribution including Apache Hadoop
Apache Hadoop & Open Source Projects
Core Hadoop, Cascading, Drill, Flume, HBase, Hive, Hue, HttpFS, Impala, Juju,
Mahout, MapReduce, Oozie, Pig, Solr, the full Spark stack, Sqoop, YARN, ZooKeeper
✔ ✔ ✔
MapR Data Platform and System Management
Performance ✔ ✔ ✔
Scalability ✔ ✔ ✔
Direct Access NFS™ ✔ ✔ ✔
Standards-based APIs and Tools ✔ ✔ ✔
Manageability ✔ ✔ ✔
Integrated Security ✔ ✔ ✔
Multi-tenancy ✔ ✔ ✔
Advanced Multi-tenancy ✔ ✔
Consistent Snapshots ✔ ✔
High Availability ✔ ✔
Disaster Recovery ✔ ✔
MapR-DB - integrated enterprise-grade NoSQL ✔ ✔
Support Features
Community Support ✔ ✔ ✔
24x7 Commercial Support ✔ ✔
MapR Solutions Resold by Teradata
© 2015 MapR Technologies 24
MapR Use Case InventoryHEALTHCARE & LIFE SCIENCES
GOVERNMENTADVERTISING, MEDIA & ENTERTAINMENT
• Improved ad targeting, analysis,
forecasting and optimization
• Personalized recommendations
• Superior analytics capability
• Enhanced game player engagement
FINANCIAL SERVICES
• Fraud Detection
• Customer Segmentation Analysis
• Customer Sentiment Analysis
• Risk Aggregation
• Counterparty Risk Analytics
• New Products and Services for
Consumer Card Holders
• Credit Risk Assessment
• 360-Degree Customer Service
• Cybersecurity, Intelligence
• Crime Prediction and Prevention
• Defense, National Security
• Pharmaceutical Drug Evaluation
• Scientific Research
• Weather Forecasting
• Fraud Detection
• Emergency Communications/Response
• Traffic Optimization
TELECOMMANUFACTURING OIL & GAS RETAIL
• Personalized Treatment Planning
• Assisted Diagnosis
• Fraud Detection
• Monitor Patient Vital Signs
• Assembly Line Quality Assurance
• Preventive Maintenance
• Supply Chain and Logistics
• Monitoring Product Quality through
Telemetry Data
• Real-time Parts Flow Monitoring
• Product Configuration Planning
• Market Pricing and Planning
• Oil Exploration and Discovery
• New oil prospect identification
• Seismic trace identification
• Oil Production
• Equipment Maintenance
• Reservoir Engineering
• Safety and Environment
• Security
• Up-Sell/Cross-Sell Recommendations
• Social Media Analysis
• Dynamic Pricing Across Multiple
Channels
• Fraud Detection
• Clickstream Analysis
• Loyalty Program Benefits
• 360° Customer View
• Operational Intelligence
• Customer Churn Analysis
• Fraud Detection
• Clickstream Analysis
• Recommendations
• Product Development
• Network Management/Optimization
© 2015 MapR Technologies 25
Cisco was able to analyze service sales opportunities in 1/10 the time, at 1/10 the cost,
and generated $40 million in incremental service bookings in the first year.
Cisco: 360° Customer ViewCisco uses integrated customer data to increase revenues
• Create shared view of customer & operations across 75,000 employees
• Increase revenue opportunities with sales partners
• Customer information was siloed in different divisions
• Customer interactions were inconsistent and not satisfying
• Missed opportunities for upselling/cross selling
• Use MapR to collect customer information across touch points
• Integrate billing, support, manufacturing, social media, websites, dial-in data
• Generate new sales leads internally and for partners
OBJECTIVES
CHALLENGES
SOLUTION
Architecture for
Sales Partner Opportunities
Business Impact
© 2015 MapR Technologies 26
Cisco Data Platforms Reference Architecture
“The entire market is starting to realize that data is everywhere and an agile ecosystem is paramount. The marketplace demands the
flexibility to meet specific needs and decisions are being made based on how well the ecosystem players are integrated.”
Arvind Bedi, Director IT, Cisco Systems
DATABASES
DOCS, CASES,
CONTENT, SOCIAL
MEDIA, CLICKSTEAM
Data Storage and Processing
ERP
SFDC
SAP HANA ON UCS
AGILE ANALYTICS
MAPR DISTRIBUTION FOR
HADOOP
Streaming(Spark
Streaming,
Storm)
MapR-DB
MAPR DISTRIBUTION FOR
HADOOP
Batch(MR, Spark,
Hive, Pig, …)
MapR-FS
BIG DATA PLATFORM
MISSION CRITICAL
REPORTING
DATA SECURITY,
INFRASTRUCTURE
CUSTOMER NETWORK,
PRODUCT USAGE
INTERNET OF
EVERYTHING (IoE)
SELF SERVICE
DASHBOARD
RAPID BUSINESS
MODEL
DATA
EXPLORATION
REAL TIME
PREDICTIVE
MISSION CRITICAL
OPERATIONAL
REPORTS
FINANCIAL
REPORTING &
EXTRACT
DATA ANALYSIS,
TEXT ANALYTICS
MACHINE LEARNING,
STATISTICAL
ANALYSIS
MACHINE DATA
INSIGHTS
FINANCIALS
STABLE CORE
CONTROLLED CHANGE
Network of
Trust
MapR Data Platform
Data ConsumptionData Sources
ALL Other Sources
Data Bases
(Mobile/ Browser/ Data Service)
Interactive(Drill, Impala)
© 2015 MapR Technologies 27
Increase in Website engagement and conversion with more relevant offers
Improved customer satisfaction and reduced churn
Higher performance (35-60% faster) & reliability for customer-facing applications
Improving the Customer Experience with Big DataLarge brokerage increases customer acquisition rate and improves customer service
• Increase conversion rate of online visitors to customers
• Provide real-time response for call center agents to service customers
• Inability to provide customers with right content through right channel
• Lack of real-time 360 view into customers
• Operational issues with prior Hadoop distribution
• Easy ingestion of customer, application and clickstream data with NFS
• Deeper insights to customer preferences across web, mobile, call center
• Real-time contextual offers to clients using MapR-DB
• Real-time streaming application for customer support with Storm on MapR
OBJECTIVES
CHALLENGES
SOLUTION
Business
Impact
LARGE BROKERAGE
© 2015 MapR Technologies 28
MAPR DISTRIBUTION FOR
HADOOP
NFS,
Sqoop, Flume MapR-DBHive &
Datameer
Ingest, Transform, Enrichment
(Batch Processing)
Interactive
analyticsOperational
Drill
MapR-FSStreaming
MapR Data Platform
MapR-FS MapR-DB
Storm
Architecture and Use Cases Data Movement
Data Access
Relevant customer
offers & experience
CUSTOMIZED
FINANCIAL PRODUCT
CONTEXTUAL
CUSTOMER SUPPORT
Real-time call
center response
CUSTOMER 360 & WEB
Web
Clickstream
(Omniture)
Application Logs
(Splunk)
Customer Data
(Teradata)
Data Sources Customer 360
database
DISTRIBUTION FOR HADOOP
160 customer attributes
Call Center Records
© 2015 MapR Technologies 30
Free on-demand
Hadoop training leading to certification
Start becoming an expert now
mapr.com/training
50MIn Free Training
© 2015 MapR Technologies 31
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