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© 2017 Symphony Health. All Rights Reserved.
QLIK QONNECTIONS 2017
JETHRO AND SYMPHONY HEALTH
Eli Singer
CEO
Jethro
Susan Davis
Director Application Development
Symphony Health
© 2017 Symphony Health. All Rights Reserved.
Jethro – Interactive BI on Big Data
• Exclusive focus: BI tools, live access, large datasets
• Success Criteria: interactive performance, high
concurrency
• Unique solution: combine 3 proven tech into one product
— Columnar SQL engine
— Search-indexing
— OLAP Cubes
• Partnerships
— BI, Hadoop, Cloud
© 2017 Symphony Health. All Rights Reserved.
• Use-case: enterprises off-loading BI apps from legacy EDW
(Teradata, Vertica) to new Big Data platforms (Hadoop,
AWS)
• Motivation: greater scale, lower cost
• Requirement: users expect same functionality &
performance SLA
• Challenges: lack of data platform performance for BI apps
• Alternatives: complex data re-engineering, expensive
external analytical DBs (Redshift), new BI paradigms (BI-as-
a-Service)
What We Hear From Customers
© 2017 Symphony Health. All Rights Reserved.
Jethro’s Value proposition
Customers use Jethro for INTERACTIVE BI ON BIG DATA:
• Works with Qlik apps “as is”
• Accelerates all types of BI queries
• Serves 1,000’s of concurrent users
• Scales to BB’s rows
While
• Responding in seconds
• Requiring no data re-engineering
EDW INTERACTIVE BI at HADOOP COST and
SCALE
© 2017 Symphony Health. All Rights Reserved.
Jethro is a transparent middle tier
between Qlik and Big data platform
• Jethro extracts data from any source (EDW,
Hadoop) and creates a highly optimized version of
the dataset
— Indexes, Auto-Cubes, Columns
— Jethro uses Hadoop, Cloud, or NFS to store it’s data
• Qlik uses Direct Discovery to send live queries to
Jethro
• Jethro resolves BI queries using its indexes and
cubes
— Never having to go back to the original source
Data
How Jethro Fits In
SQL
Cloud
Data
© 2017 Symphony Health. All Rights Reserved.
Heavy Lifting Done in Background, Less Effort for Live Queries
useruserusers
Cubes, Indexes,
Cache
Tables, Files, Streams
Full-Scan
Data Lake
Interactive
Background:
Build indexes,
cube aggregations
Live Query:
Process query from pre-
computed indexes,
cubes
For Data that is written once and read thousands of
times, it is far better to focus the effort at write time
© 2017 Symphony Health. All Rights Reserved.
Must Have Both Cubes AND Indexes for Interactive BI
Highly
Aggregated
Highly
Granular
Cubes Indexes select … where
cust_id=123456
sum(sales) …
group by state
Cubes and Indexes perfectly compliment each other
• Index’s strength – multiple filters, hi-cardinality cols – are cube’s weakness
• Cube’s strength – few-to-no filters, low-cardinality cols – are index’s weakness
Query Type
Query example: Query example:
© 2017 Symphony Health. All Rights Reserved.
BI on Hadoop Alternatives
Full-Scan Full-Scan
Auto
Cube
Slow
Index
OLAP Cubes-on-Hadoop
Fast
SQL-on-Hadoop
Manual
Cube
© 2017 Symphony Health. All Rights Reserved.
QLIK QONNECTIONS 2017
JETHRO AND SYMPHONY HEALTH
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved. 10
 Symphony Health provides thorough data and powerful
analytics to help professionals understand the full market
lifecycle including:
‐ predictive market analysis
‐ patient influence
‐ physician prescribing
‐ pharmacy fulfillment
‐ payer reimbursement
‐ sales compensation
Symphony Health Overview
© 2017 Symphony Health. All Rights Reserved.
 7 Billion TRXs yearly
 Over 4+ petabytes of data stored
 2 petabytes of data in Integrated DataVerse (IDV)
- Prescription and Medical and Hospital Claims Data
 Reporting Database represents linkages between the patient actions,
products, prescribers, pharmacies/facilities, and payer plans
 Over 900 concurrent users for Decision Flow and Vantage apps
SHS Reporting Data
11
© 2017 Symphony Health. All Rights Reserved.
 BI Technologies
- Qlik Sense/Qlik View
- Micro Strategy
- Tableau
- Custom Reporting Tools
 Data Storage Technologies
- Hadoop
- Oracle
- Cloud Providers/Computing
- Flat Files
Current Reporting Technology Stack
12
© 2017 Symphony Health. All Rights Reserved.
 Poor visualizations for some
 Customizations difficult to manage
 Requires technology savvy users
- detailed training session required and additional hands on assistance to
build even simple reports
 Long run times
- Some reports take so long to render they need to run in background (up to
5+ hours to generate)
 Large volumes of data
 Multiple data stores require complex joins and connections
 Number of concurrent users cause significant increases in run times
 Users have the ability to build custom metrics with poor logic and
referential integrity issues causing system wide failures
BI Tool Challenges
13
© 2017 Symphony Health. All Rights Reserved.
BI Application Process
14
Live Connection
via
Direct Discovery
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved. 15
“At Symphony Health, Jethro gives us the ability to build custom
reports and data visualizations interactively with real time
results. Jethro allows our analysts to provide thoughtful
insights on vast amounts of data and to provide our customers
with actionable results significantly faster than before.”
Jethro and Symphony Health
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved. 16
Jethro Benefits
Proprietary index-access architecture
Adaptive caching
Dynamic capability to scale for concurrency
Bottom line….Jethro allows us to offer interactive Business
Intelligence on huge volumes of data to our customers
improving our reliability, and customer relationships by
empowering them to have access to the data they need.
© 2017 Symphony Health. All Rights Reserved.
Timing and Cost Savings with Jethro
17
 Time Savings Noted with Decision Flow Application
 Cost Savings noted with Qlik View Application:
- Approximately $48,000 savings yearly for hardware and memory.
Average Without
Jethro
Average With
Jethro
Average
% Time Savings
Up to 2 minutes < 15 seconds 97%
Between 2-6
minutes
2 minutes 56%
© 2017 Symphony Health. All Rights Reserved.
 Contains transaction level prescription and claims information
linked to an anonymous patient ID
 Includes both extracted and derived metrics
 Data populated is historical for latest 24 months
 Currently delivering:
- 26 Prescription based applications
- 21 Diagnosis based applications
- 20 Persistency and Compliance (Source of Business) applications
- 5 Product Level Prescription with Diagnosis applications
Decision Flow - Patient Transaction Dataset (PTD)
18
© 2017 Symphony Health. All Rights Reserved.
 Non-market specific (all products) prescription based tool
 Provides insights into practitioner, payer, and product data
 Data populated is for latest 24 months
 Reporting data contains:
- Over 10,000 unique products
- 8 Billion rows of data
Corporate Vantage – Practitioner Insights
19
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved.
© 2017 Symphony Health. All Rights Reserved.
Thank you
20
© 2017 Symphony Health. All Rights Reserved.
Demo Decision Flow
21
© 2017 Symphony Health. All Rights Reserved.
Demo Decision Flow
22
© 2017 Symphony Health. All Rights Reserved.
Demo Decision Flow
23
© 2017 Symphony Health. All Rights Reserved.
Demo Corporate Vantage
24

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Jethro + Symphony Health at Qlik Qonnections

  • 1. © 2017 Symphony Health. All Rights Reserved. QLIK QONNECTIONS 2017 JETHRO AND SYMPHONY HEALTH Eli Singer CEO Jethro Susan Davis Director Application Development Symphony Health
  • 2. © 2017 Symphony Health. All Rights Reserved. Jethro – Interactive BI on Big Data • Exclusive focus: BI tools, live access, large datasets • Success Criteria: interactive performance, high concurrency • Unique solution: combine 3 proven tech into one product — Columnar SQL engine — Search-indexing — OLAP Cubes • Partnerships — BI, Hadoop, Cloud
  • 3. © 2017 Symphony Health. All Rights Reserved. • Use-case: enterprises off-loading BI apps from legacy EDW (Teradata, Vertica) to new Big Data platforms (Hadoop, AWS) • Motivation: greater scale, lower cost • Requirement: users expect same functionality & performance SLA • Challenges: lack of data platform performance for BI apps • Alternatives: complex data re-engineering, expensive external analytical DBs (Redshift), new BI paradigms (BI-as- a-Service) What We Hear From Customers
  • 4. © 2017 Symphony Health. All Rights Reserved. Jethro’s Value proposition Customers use Jethro for INTERACTIVE BI ON BIG DATA: • Works with Qlik apps “as is” • Accelerates all types of BI queries • Serves 1,000’s of concurrent users • Scales to BB’s rows While • Responding in seconds • Requiring no data re-engineering EDW INTERACTIVE BI at HADOOP COST and SCALE
  • 5. © 2017 Symphony Health. All Rights Reserved. Jethro is a transparent middle tier between Qlik and Big data platform • Jethro extracts data from any source (EDW, Hadoop) and creates a highly optimized version of the dataset — Indexes, Auto-Cubes, Columns — Jethro uses Hadoop, Cloud, or NFS to store it’s data • Qlik uses Direct Discovery to send live queries to Jethro • Jethro resolves BI queries using its indexes and cubes — Never having to go back to the original source Data How Jethro Fits In SQL Cloud Data
  • 6. © 2017 Symphony Health. All Rights Reserved. Heavy Lifting Done in Background, Less Effort for Live Queries useruserusers Cubes, Indexes, Cache Tables, Files, Streams Full-Scan Data Lake Interactive Background: Build indexes, cube aggregations Live Query: Process query from pre- computed indexes, cubes For Data that is written once and read thousands of times, it is far better to focus the effort at write time
  • 7. © 2017 Symphony Health. All Rights Reserved. Must Have Both Cubes AND Indexes for Interactive BI Highly Aggregated Highly Granular Cubes Indexes select … where cust_id=123456 sum(sales) … group by state Cubes and Indexes perfectly compliment each other • Index’s strength – multiple filters, hi-cardinality cols – are cube’s weakness • Cube’s strength – few-to-no filters, low-cardinality cols – are index’s weakness Query Type Query example: Query example:
  • 8. © 2017 Symphony Health. All Rights Reserved. BI on Hadoop Alternatives Full-Scan Full-Scan Auto Cube Slow Index OLAP Cubes-on-Hadoop Fast SQL-on-Hadoop Manual Cube
  • 9. © 2017 Symphony Health. All Rights Reserved. QLIK QONNECTIONS 2017 JETHRO AND SYMPHONY HEALTH
  • 10. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. 10  Symphony Health provides thorough data and powerful analytics to help professionals understand the full market lifecycle including: ‐ predictive market analysis ‐ patient influence ‐ physician prescribing ‐ pharmacy fulfillment ‐ payer reimbursement ‐ sales compensation Symphony Health Overview
  • 11. © 2017 Symphony Health. All Rights Reserved.  7 Billion TRXs yearly  Over 4+ petabytes of data stored  2 petabytes of data in Integrated DataVerse (IDV) - Prescription and Medical and Hospital Claims Data  Reporting Database represents linkages between the patient actions, products, prescribers, pharmacies/facilities, and payer plans  Over 900 concurrent users for Decision Flow and Vantage apps SHS Reporting Data 11
  • 12. © 2017 Symphony Health. All Rights Reserved.  BI Technologies - Qlik Sense/Qlik View - Micro Strategy - Tableau - Custom Reporting Tools  Data Storage Technologies - Hadoop - Oracle - Cloud Providers/Computing - Flat Files Current Reporting Technology Stack 12
  • 13. © 2017 Symphony Health. All Rights Reserved.  Poor visualizations for some  Customizations difficult to manage  Requires technology savvy users - detailed training session required and additional hands on assistance to build even simple reports  Long run times - Some reports take so long to render they need to run in background (up to 5+ hours to generate)  Large volumes of data  Multiple data stores require complex joins and connections  Number of concurrent users cause significant increases in run times  Users have the ability to build custom metrics with poor logic and referential integrity issues causing system wide failures BI Tool Challenges 13
  • 14. © 2017 Symphony Health. All Rights Reserved. BI Application Process 14 Live Connection via Direct Discovery
  • 15. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. 15 “At Symphony Health, Jethro gives us the ability to build custom reports and data visualizations interactively with real time results. Jethro allows our analysts to provide thoughtful insights on vast amounts of data and to provide our customers with actionable results significantly faster than before.” Jethro and Symphony Health
  • 16. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. 16 Jethro Benefits Proprietary index-access architecture Adaptive caching Dynamic capability to scale for concurrency Bottom line….Jethro allows us to offer interactive Business Intelligence on huge volumes of data to our customers improving our reliability, and customer relationships by empowering them to have access to the data they need.
  • 17. © 2017 Symphony Health. All Rights Reserved. Timing and Cost Savings with Jethro 17  Time Savings Noted with Decision Flow Application  Cost Savings noted with Qlik View Application: - Approximately $48,000 savings yearly for hardware and memory. Average Without Jethro Average With Jethro Average % Time Savings Up to 2 minutes < 15 seconds 97% Between 2-6 minutes 2 minutes 56%
  • 18. © 2017 Symphony Health. All Rights Reserved.  Contains transaction level prescription and claims information linked to an anonymous patient ID  Includes both extracted and derived metrics  Data populated is historical for latest 24 months  Currently delivering: - 26 Prescription based applications - 21 Diagnosis based applications - 20 Persistency and Compliance (Source of Business) applications - 5 Product Level Prescription with Diagnosis applications Decision Flow - Patient Transaction Dataset (PTD) 18
  • 19. © 2017 Symphony Health. All Rights Reserved.  Non-market specific (all products) prescription based tool  Provides insights into practitioner, payer, and product data  Data populated is for latest 24 months  Reporting data contains: - Over 10,000 unique products - 8 Billion rows of data Corporate Vantage – Practitioner Insights 19
  • 20. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. © 2017 Symphony Health. All Rights Reserved. Thank you 20
  • 21. © 2017 Symphony Health. All Rights Reserved. Demo Decision Flow 21
  • 22. © 2017 Symphony Health. All Rights Reserved. Demo Decision Flow 22
  • 23. © 2017 Symphony Health. All Rights Reserved. Demo Decision Flow 23
  • 24. © 2017 Symphony Health. All Rights Reserved. Demo Corporate Vantage 24