Datameer 6 is completely re-imagining the user experience for modern BI, helping you deliver new insights faster and more results to your data-hungry business. During this one-hour webinar, we demonstrated all that's new with Datameer 6 and how you can: Discover answers to a new range of business questions using an iterative, exploratory approach Find answers faster and deliver more insights with a new faster analytic workflow Utilize Spark to speed analytic processing time without needing to know technical details Watch this on-demand webinar, with special guest speaker, Sean Anderson, Senior Product Marketing Manager, from Cloudera, who discusses Cloudera's view of the Hadoop data processing stack and how the market place is benefiting from Spark.

1. © 2016 Datameer, Inc. All rights reserved.
John Morrell, Senior Director of Product Marketing
Sean Anderson, Senior Product Marketing Manager
Datameer 6 - The Modern BI Platform for Your Big
Data Journey
© 2016 Datameer, Inc. All rights reserved.

2. © 2016 Datameer, Inc. All rights reserved.
About the Speakers
John Morrell
Senior Director
Product Marketing
Sean Anderson
Senior Product
Marketing Manager

3. © Cloudera, Inc. All rights reserved. 3
Spark will replace MapReduce
To become the standard execution engine for Hadoop

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Data Processing
Data may require unique processing characteristics
▪ Batch
▪ Streaming
▪ Real-time
Hadoop arose to address one and now the ecosystem
is answering the rest.
▪ “We’re doubling down on Spark. We invested earliest,
and we’ve invested most, in making Hadoop
enterprise-grade” Doug Cutting
Data Processing
Leverage the right processing for your job

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Powerful Data Processing - The Most Apache Spark
Experience
5
STRUCTURED
Sqoop
UNSTRUCTURED
Kafka, Flume
PROCESS, ANALYZE, SERVE
UNIFIED SERVICES
RESOURCE MANAGEMENT
YARN
SECURITY
Sentry, RecordService
FILESYSTEM
HDFS
RELATIONAL
Kudu
NoSQL
HBase
STORE
INTEGRATE
BATCH
Spark, Hive,
Pig
MapReduce
STREAM
Spark
SQL
Impala
SEARCH
Solr
SDK
Kite
Spark: In-memory data processing for developers
and data scientists
• Easy development
• Flexible, extensible API
• Fast batch and stream processing
Cloudera: Most experience with Spark on Hadoop
for instant success
• First to ship and support
• Most Spark users trained
• Most customers running Spark
• Most engineering resources (committers, contributors, support)
• Only vendor focused on enterprise Spark

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Apache Spark
Cloudera was the first Hadoop vendor to ship and support Spark
• Spark is a fully integrated part of Cloudera’s platform
• Shared data, metadata, resource management, administration, security,
and governance
• Complements specialized analytic tools for comprehensive big data platform
• Cloudera is the first Hadoop vendor to offer Spark training
• Trained more customers than any other vendor
• Most popular training course
• Cloudera has 5x the engineering resources of the next competitor
• Most committers on staff and most changes contributed
• Well-trained staff across the globe with expertise implementing a broad range
of Spark use cases

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Cloudera’s Engineering Commitment to Spark
7

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The Spark Ecosystem & Hadoop
8
STRUCTURED
Sqoop
UNSTRUCTURED
Kafka, Flume
UNIFIED SERVICES
RESOURCE MANAGEMENT
YARN
SECURITY
Sentry, RecordService
FILESYSTEM
HDFS
RELATIONAL
Kudu
NoSQL
HBase
STORE
INTEGRATE
SQL
Impala
SEARCH
Solr
SDK
Kite
BATCH & STREAM
Spark
Spark
Streaming Spark SQL DataFrames MLlib …

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Uniting Spark and Hadoop - The One Platform Initiative Investment
Areas
9
Management
Leverage Hadoop-native
resource management.
Security
Full support for Hadoop security
and beyond.
Scale
Enable 10k-node clusters.
Streaming
Support for 80% of common stream
processing workloads.

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Community Initiative: Spark Supersedes
MapReduce
10

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Key Cloudera Contributions
11
• Spark-on-YARN integration
• Dynamic Resource
Allocation
• Kafka Integration
• HBase Integration
• Fixed operational issues at
scale
Integration with Hadoop
Ecosystem
Production-Ready Features Ongoing Initiatives
• Security
• Kerberos Integration
• HDFS Sync (Sentry)
• Governance
• Cloudera Navigator integration
(audit & lineage)
• Monitoring/Troubleshootin
g
• Improved debugging
• Zero Data Loss
• Spark Streaming Resilience
• Standard Execution Engine
• Hive on Spark
• Pig on Spark
• Crunch on Spark
• Solr indexing on Spark

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Cloudera Customers
12
• More customers running Spark than all other vendors combined
• Over 170 customers
• Spark clusters as large as 800 nodes
• Diverse range of use cases across multiple industries
• Search personalization
• Genomics research
• Insurance modeling
• Advertising optimization
• Predictive modeling of disease conditions

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Cloudera Enterprise, A New Way Forward
13

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Key Cloudera Contributions
14
① ②
Download or Deploy
in the Cloud
Signup for Training Contact us or a Partner
to Start a POC
③
Getting Started is Easy

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Datameer 6:
The Modern BI Platform for Your Big Data
Journey

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Big Data Journey Challenges
Meeting
Demand
(Productivity)
Putting Your
Insights to
Work
Answering
New
Questions
Using More
of Your Data
Skill Gaps

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Deep New-Age Questions
• What journey do customers take to purchase products?
• What actions do customers take before they churn?
• What attributes do customers with similar buying behavior have in common?
• Why do certain assets have a large impact on our overall risk?
• What series of events occur before equipment fails?
• Where are my network bottlenecks and how does this impact service?

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More Data Sources
Business Data
Digital Interactions
Machine Data
Marketing Call Center Web Social Media
Devices IT Sensors Security Network
CRM Sales Financial
…
…
…

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Datameer: Fastest Time to Insight
Time
Complexity
4 weeks 8 weeks 12 weeks 18 months
$$$
$$
$
Enterprise Data Warehouse
ETL Data Warehouse BI
Use
Case
#2
Use
Case
#3
Use
Case
#4
Use
Case
#5
Datameer Use Case #1
Use Case #1
Use
Case
#6
Use
Case
#7
Use
Case
#8
Use
Case
#9
6 weeks 10 weeks
Integrate Analyze Visualize
Use Case #2 Use Case #3
Custom Big Data
Flume Hive Pig Sqoop Raw Data Hadoop
NO
CODIN
G

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End-to-end Modern BI Platform
Integrate
• 70+ Connectors
• Wizard-led
• Unstructured data
• High Performance
Prepare/Analyze
• 270+ Functions
• Instant Profiling
• Familiar Spreadsheet
UI
• Advanced analytics
• Smart Data Discovery
Visualize
• 30+ Widgets
• Infographics
• HTML 5
Operationalize
• Security
• Governance
• Process integration

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Agile Self-Service Analytics without Chaos
Spreadsheet Collaborative Governance & ControlDrag-n-Drop

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Advanced Analytics & Smart Data Discovery
Clustering Decision Trees Dependencies Recommendations
Time Series Analytics Graph & Path Analytics Text Analytics

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Augment Existing Analytics
Visualization &
Exploration
Traditional BI

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Enterprise Ready
Integrate,
Don’t Replace
Intelligent
Execution Framework
Flexible
Deployment Options

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What’s New in Datameer 6?
Make Big Data Simple for Everyone
Speed-to-InsightEase-of-Use
Re-imagined User
Experience & Workflow
Spark
Enable Citizen Data Scientists Abstract Complexity

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Smart Execution with Spark

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Differences in Spark Implementations
BI on Spark Spark Cluster
Embedded
Spark
Smart
Execution
Spark
• Limited to structured
view of data
• Like using Hive or
Impala in Hadoop
• Fully programmatic
approach
• Need specialized
skills $$
• May force you to
code at points
• No future-proof story
• Limited execution
frameworks
• Eliminates technical
complexities
• Don’t need
specialized skills
• Optimizes
execution/performanc
e

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New Backend Benefits
Future-proof
Fastest
processing, every
time
Concentrate on
analytics, not
backend
Abstract Complexity

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Why does UI and Workflow Matter?
“That is the way to learn the most,
that when you are doing something
with such enjoyment that you don’t
notice the time passes.”

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The Evolution of Analytic Workflow
Integrate Transform Analyze Visualize
1st Generation:
Multiple Steps
2nd Generation:
Self-Service
3rd Generation:
Iterative/Fluid

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Datameer 6 User Experience
Parallel Workflow
Immediate insight
into downstream
effects
Fresh, Modern
UI/UX
Significant Time Savings Increased Productivity

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Demonstration

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Learn More
http://www.datameer.com/product/datameer-6/

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Thank You!