The document outlines Sqrrl's capabilities and methodology for building big data applications, emphasizing strong security, scalability, and efficient data interactions. It highlights the importance of defining business objectives, user roles, and datasets while providing a step-by-step approach to data management, from loading to evaluation. Sqrrl positions itself as an expert in transforming big data into actionable insights through its enterprise solutions.

1. Securely explore your data
BUILDING BIG APPS®
WITH SQRRL
ENTERPRISE
Data-Driven Processes to Making Your Big Data Actionable
Joe Travaglini, Director of Product Marketing
3/27/2014

2. OUTLINE
• Brief Company and Product Overview
• Setting Context: The “Big Promise”
• Steps for Building a Big App
• How Sqrrl can help
2© 2014 Sqrrl Data, Inc. | All Rights Reserved

3. COMPANY OVERVIEW
© 2014 Sqrrl Data, Inc. | All Rights Reserved 3

4. WHO WE ARE
© 2014 Sqrrl Data, Inc. | All Rights Reserved
Sqrrl’s team has worked with the world’s largest
and most sensitive datasets for the last decade
" Over 20 years of combined
Accumulo experience
" Team includes former Technical
Director of Accumulo at NSA and
6 committers/contributors
Google’s
BigTable Paper
2006
NSA Builds
Accumulo
2008
Sqrrl Founded
2012
1st Sqrrl Release
and Customers
2013
NSA Open
Sources
Accumulo
2011
Investors:
4

5. OUR KEY FEATURES
© 2014 Sqrrl Data, Inc. | All Rights Reserved
Sqrrl Enterprise has best-in-class security,
scalability, and flexibility
5
Data-Centric Security
Unprecedented Scale and Rates of Ingest
Automated Labeling and Indexing
Secure Full-Text and Graph Search
Column, Document, and Graph Data Models
Query: SqrrlQL
Analytics: Real-Time Aggregates and Hadoop Integrations

6. SETTING CONTEXT
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7. THE “BIG PROMISE”
“We entered the age of Big Data when the
opportunity cost of throwing data away
exceeded the monetary cost of keeping it…”
… but how do we take advantage of the data to realize the
opportunity?
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How can we make Big Data fulfill the hype?

8. A PROPOSED SOLUTION
• Data Lake as one-stop shop for all things data
• Great in theory, difficult in practice:
• How do you catalog and search data from different
origins?
• What controls are in place for security/compliance?
• How do you turn a big filesystem into a useful
application?
• If you don’t have good answers to the above, you
are now the proud owner of a Data Landfill
© 2014 Sqrrl Data, Inc. | All Rights Reserved 8
…Enter the Data Lake / Data Hub

9. KEYS TO SUCCESS
• Robust security
• Easy ways to acquire data
• Easy ways to retrieve data
• Compelling ways to interact with data
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Our Core Values and Areas of Focus

10. BUILDING A BIG APP
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OK then…

11. BUILDING A BIG APP
1. Define the business objective
! Spell out your goals, outcomes, metrics, KPIs
2. Define users and roles
! What are the classifications of users of your app?
! What actions do they need to perform?
" Strive for specificity
3. Identify relevant datasets
! Specify partial schemas where appropriate
! Consider which fields are most important to index
! Consider data volume for proper capacitization
© 2014 Sqrrl Data, Inc. | All Rights Reserved 11
Our Methodology for tackling Big Data Problems

12. TUTORIAL
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Dataset Creation in Sqrrl

13. BUILDING A BIG APP, CON’T
4. Determine access policies for the data
! Granular Cell-Level Security Enforcement
! Attribute-based Access Control
5. Load the Data
! Access Labeling and Indexing
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Our Methodology for tackling Big Data Problems

14. TUTORIAL
• Rules file:
• Bulk import:
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Bulk Loading in Sqrrl

15. TUTORIAL
Note that username and
bytesUp are not visible
to this user!
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Bulk Loading Results

16. BUILDING A BIG APP, CON’T
4. Determine access policies for the data
! Granular Cell-Level Security Enforcement
! Attribute-based Access Control
5. Load the Data
! Access Labeling and Indexing
6. Transform the Data
! More often than not
7. Syndicate the Data
! Use the Sqrrl Thrift API to wire a front-end
! Export the data to HDFS, downstream systems
© 2014 Sqrrl Data, Inc. | All Rights Reserved 16
Our Methodology for tackling Big Data Problems

17. BUILDING A BIG APP, CON’T
8. Peruse the data
! Our query language: SqrrlQL
" Real-time, Secure Text Search
" Graph Search
" Summaries / Filters
9. Evaluate and Refine
! Did I answer the questions I wanted?
! Did the results match expectations?
! Are there new questions to ask?
10. Rinse and Repeat
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Our Methodology for tackling Big Data Problems

18. RECAP
• Start your journey with specific goals in mind
• Big Data can get bigger – and usually does
• Data-Centric Security enables comfortable
consolidation and integration
• Real-time search, discovery, and analytics are the
core of Big Apps
• Sqrrl is here to help!
© 2014 Sqrrl Data, Inc. | All Rights Reserved 18

19. WHAT’S NEXT
April’s Webinar: Healthcare Apps
with Medyear by Personiform
powered by Sqrrl Enterprise
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20. THANKS!
FOR MORE INFO:
• Visit us at http://www.sqrrl.com
• Follow us on Twitter -- @SqrrlData
• Send us an email: info@sqrrl.com
Presented by:
JOE TRAVAGLINI
Director of Product Marketing
jtrav@sqrrl.com
@joe_travaglini
© 2014 Sqrrl Data, Inc. | All Rights Reserved 20