EXPAND FOR MORE INFO. Speaker: Phong Vu, HPE Big Data Applications Meetup, 03/16/2014 Palo Alto, CA More info here: http://www.meetup.com/BigDataApps/ Link to video: https://www.youtube.com/watch?v=nQHO4__A5js About the talk: HPE Haven OnDemand is a platform for building data-rich applications and analytics using text analysis, speech recognition, image analysis, indexing and search APIs. Simply put, developers and businesses use the Haven OnDemand APIs to add advanced capabilities such as natural language processing, machine learning, and predictive analytics to their applications. This talk will focus on Haven OnDemand platform’s capabilities of human information analytics and building advanced unstructured text indexes.

1. Haven OnDemand
Leverage Human Information and Big Data Analytics
Phong Vu – Developer Evangelist @ HPE – Haven OnDemand
@pacovu

2. 2
Is a cloud computing platform for understanding and analyzing unstructured human information, machine
and business data.
Provides developers with powerful functionality delivered by a scalable multi-tenant PaaS accessed on-
demand via APIs.
Haven OnDemand
You build,
host,
manage, and
maintain
Traditional
solutions
On-Demand
Automation

3. 3
Unstructured Data
Human Data
● Document files
● Emails
● Plain text
● SQL text fields
● JSON, XML, etc
● Scans
● Voice recordings
● Videos
Haven OnDemand

4. 4
FORMAT
CONVERSION
AUDIO/VIDEO
ANALYTICS
PROFILE &
MANIPULATION
IMAGE
ANALYSIS
CONNECTORS
TEXT
INDEXING
UNSTRUCTURED
TEXT
ANALYSIS
PREDICTION
GRAPH
ANALYTICS
POLICY
SEARCH
Over 60 APIs – www.havenondemand.com
Connect, Extract, Index, Search, & Analyze.

5. Haven OnDemand Categorized Capabilities
5
Audio/Video
analytics
Image
analytics
Text
analysis
Search
Graph
analysis
Format
Conversion
Unstructured
Text Indexing
public/private
indexes
Policy
Management
Query Profile
datasets
Prediction
doc/reference
doc/reference
doc/reference
Connectors
cloud
on-site

6. HOD Clients – bit.ly/hpe-github
6

7. Sentiment Analysis - example
7
The following is a random hotel review from TripAdvisor:

8. Sentiment Analysis – example
8
strongly negative quite negative quite positive strongly positiveneutral
-1 0 1

9. Unstructured data into Structured data
“Public transportation system in
San Francisco is very effective”
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10. Unstructured Text Indexing
– Index content to make it available for search APIs
– Create Text Index
– Add to Text Index
– Delete Text Index
– Delete from Text Index
– Index Status
– List Resources
– Restore Text Index
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11. Connectors
– Connect and retrieve data across disparate content repositories
– web_cloud
– dropbox_cloud
– filesystem_onsite
– sharepoint_onsite
– Start manually or automatically by scheduler
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C1
C2
My index

12. Net Promoter Score survey results analysis
Use case
12

13. Call center data analytics
Use case
13

14. E-Discovery
Use case
14

15. Rich Media Player Demo for Windows 8.x/10
15
URL for Windows 10 https://www.microsoft.com/store/apps/9nblggh5lb4q
URL for Windows 8.x http://apps.microsoft.com/windows/app/ddf3ffa9-dcef-40ae-8711-f5eb5c7e1a73

16. Thank you
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