red hat in financial services - presentation at hortonworks booth - strata 2014
DESCRIPTION
This presentation gives an overview of how Hortonworks and Red Hat have collaborated to provide the financial services industry with Big Data solutions.TRANSCRIPT
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Financial Services Industry Solution -Risk Management
Liquidity Risk
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Liquidity Risk - The Definition
“Liquidity risk is financial risk due to uncertain liquidity.
An institution might lose liquidity if its credit rating falls, it experiences sudden unexpected cash outflows, or some other event causes counterparties to avoid trading with or lending to the institution. A firm is also exposed to liquidity risk if markets on which it depends are subject to loss of liquidity.”
(http://en.wikipedia.org/wiki/Liquidity_risk)
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Liquidity Risk - Business Challenge
● We need the ablility to run Liquidity Risk Algorithms on our Investment Portfolios at many different intervals
○ Intra Day; End of Day; Weekly; Monthly; Quarterly; Annual
● In support of ○ maximizing investment opportunities○ satisfying regulatory capital reserve requirements
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Liquidity Risk Calculations Demo Setup
We are actively ingesting real time market feeds into the architecture.
We will show:
● Intra Day Liquidity Risk Algorithms executing In Memory.● Batch Liquidity Risk Algorithms executing in the Data Lake.● Interactive SQL Queries showing Liquidity Risk Algorithm output.
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Overall Liquidity Risk Workflow
New Markets Data &
Portfolio Data &
Reference Data
Red Hat JBoss
Data Grid
HDP
Business Users
(3.) In-Memory calculations take place within Red Hat JBoss Data Grid. Results are routed to HDP for future Interactive and Batch job flows.
(2.) Data Transformations take place in HDP. Data flows back and forth between the Red Hat JBoss Data Grid In Memory Compute Tier and HDP.
(1.) The Red Hat JBoss Data Grid and Hortonworks Data Platform (HDP) are primed with Real Time and Batch Loads
(4.) Interactive SQL Queries and Batch Job Execution take place within HDP.
RDBMS
Optional Flow of Output Data to RDBMS systems
(5.) Business Users leverage BI Tools to Query Data Interactively in HDP and / or an RDBMS
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Liquidity Risk: High Level Topology
Hortonworks Data Platform (HDP)
RDBMS
MPP
EDW
Gov
erna
nce
& In
tegr
atio
n
Secu
rity
Ope
ratio
nsData Access
Data Management
Red Hat JBoss Fuse(ESB)
Red Hat JBoss BPMS(CEP)
Red Hat JBoss Data Grid (In-Memory Compute)
Red Hat JBoss BRMs (Workflow)
Applications Analytics
Event Stream and Batch Loads
Red Hat JBoss Data Virtualization
(ODBC, JDBC)
(Infinite Scale Storage and Compute)
Application Tier
Data Tiers
Data Ingestion
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Liquidity Risk: Data Flow and Architecture
Infinite StorageRed Hat Storage or
HDFS
Input Feed
Interactive SQL
Hive
Output Feed
Red Hat JBoss BPMs
Write Once Read Many
Batch
Red Hat JBoss BRMS(CEP)
Red Hat JBoss Data Grid
Write Many Read Many
In Memory
RDBMS EDW MPP
Applications Analytics
Red Hat JBoss Fuse(ESB) HDP
Red Hat JBoss Data Virtualization
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DEMO
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Appendix: FOR BUILD TEAM DISCUSSIONSE LAPTOP (Red Hat SE’s - 32GB RAM; Hortonworks SEs - 16 GB RAM)
Hortonworks Sandbox - HDP2.1● HiveServer2
MySQL RDBMS
Red Hat JBoss Data Virtualization
Red Hat JBoss Data Grid
SQuirrel
Libre Office
Note: Phase 2 (and for Fraud Solution) - Can add BI Partner and Red Hat JBoss BPMs, Red Hat JBoss Fuse
PHASE 1 BUILDOUT