1) The document discusses how Apache Spark is enabling enterprises to analyze large amounts of data from a variety of sources in real-time to gain insights. 2) It provides examples of how companies are using Spark for applications like online ad personalization, web log analysis, and predictive analytics. 3) The document also outlines trends in Spark adoption in enterprises and strategies for Hortonworks to help further Spark's capabilities and make it easier for enterprises to implement agile analytics and data science.

1. Accelerating Enterprise Spark
Shaun Connolly
Hortonworks Strategy
@shaunconnolly

2. Apache Spark Unlocks Enormous
Potential of Data in the Enterprise

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Personalized
Online Ads
Petabytes of
Weblogs Analyzed
with Spark at Scale
• Data streams from a vast array of
desktop and mobile devices
• 13 billion daily events processed
latency as low as 40 milliseconds
• No data cleansing necessary prior
to analysis with Apache Spark
• 2 clusters consolidated into 1
YARN-based HDP cluster
• Launched new product Webtrends
Explore™ -- powered by HDP
Per-Customer
Click Path
Web Log
Analysis
SQL Server
Offload
“We’re able to…look at this data set and process it and do predictions,
behavioral analysis. We can do things that allow us to determine ROI for
different actions and behavioral patterns.”
Peter Crossley, Chief Architect
Behavioral
Segmentation
Ad Click
Predictions
LCV
Analysis

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New Use CasesCable Company: Optimize Advertising
• Monitor channel changes with Spark Streaming
• Correlate changes with Ads/Programming
• Allocate Ads real time: Show ads to user who are
watching a show and will stay for > over 20 seconds
Railroad Company:
Real-time View of State of Track
• Optimize the track and train maintenance
• Large volume and granularity of track data
• GeoSpatial analytics is critical

5. Spark Trends
Implications for the Enterprise
Data API Enterprise Ready /
”Hardened”
Data Science is
still the Frontier

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ETL, Streaming, Reporting, Analytics
Must Integrate into Existing Environments
A Critical Tool in the Enterprise Tool Box
The Data API

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HA, DR, Tooling, Debugging, Operations
Security, Encryption, Governance Models
Scale
Implications of Enterprise-Ready / “Hardened”

8. Agile Analytics & Data Science
Need to Democratize
Easy and Better Tooling
Train and Encourage More People to Join Us

9. Hortonworks Strategy for Enterprise Spark at Scale
Agile Analytics & Data Science
Accelerate Capabilities for the Enterprise
Innovate at the Core

10. Stay tuned…. March 1

11. Thank You!
Shaun Connolly
@shaunconnolly