http://bit.ly/18kESMW – Learn how Hunk and the MapR data infrastructure can improve risk management for financial institutions by being dynamic, iterative, and responsive to change.
3. Today’s Speakers
3
Brett Sheppard
– Director Big Data Product Marketing
– Splunk
– @zettaforce
Sameer Nori
– Senior Product Marketing Manager
– MapR
– @sameernori
4. Risk Management Challenges
4
What are your bank’s biggest risk management challenges?
Respondents were asked to select no more than three
Source: FIS, April 2014
6. Current Data Infrastructure Limits Risk Management
6
Liquidity Risk
• Firm wide view of
liquidity is inhibited
by siloed systems
and lack of
actionable
information
Operational Risk
• Need to link
operational risk
with requirements
from Basel 2 and
Basel 3
Credit Risk
• Need to enhance
credit risk models
with external data
sets to get a
granular view
7. 7
Store
• Archive large
volumes of raw
granular data
• Store cost effectively
for months or years
• Secure non-public or
regulated
information
Analyze
• Explore, analyze and
visualize data
• Avoid fixed schemas
that may miss data
or limit flexibility
• Search across both
Hadoop and NoSQL
data stores
Iterate
• Respond to changes
on the fly
• Preview results
before MapReduce
jobs are complete
• Self-service analytics
vs. months of
programming
Hunk + MapR Data Infrastructure
Data infrastructure supporting risk management approaches
that are dynamic, iterative and responsive to change
8. Explore, Analyze and Visualize Data
Security &
Compliance
Digital
Intelligence
Business
Analytics
Risk Mgt. Security &
Compliance
360-degree
Customer
View
Developer Platform (REST API, SDKs)
Hadoop Clusters NoSQL and Other Data Stores
Hadoop Client Libraries Hunk Apps
Product and
Service
Analytics
Internet of
Things
8
9. Financial Services Firms Drive Results with Splunk
Troubleshootandmonitortradingandsettlementapplications. ImproveuptimeandreduceMTTR.
Monitorandmanageonlineinvestmentapplicationandservers.
Networksecuritymonitoringandrapidincidentresponsetomitigatesecurityrisks.
Ensures effective compliance while improving productivity of compliance team.
Endtoendmonitoringacrosstradingapplications–improvinguptimeandcustomerexperience.
Cross-tiervisibilitytoimprovedevopscoordinationandaccelerateMTTR.
IndexdataacrosstradingapplicationsandFIXorderprocessingtoimprovecustomerservice.
9
10. Hunk Risk Management Analytics
Enables non-technical users to build complex
reports without learning the search language
Provides more meaningful representation
of underlying raw machine data
Preview results and interactively search
across one or more clusters
Pivot
Data
Model
Interactive
Search
11. Interactively Question Data in Hadoop
Pause means stop fetching results
Stop means treat the current results
as final and end the MapReduce job
12. Hunk Applies Schema on the Fly
• Structure applied at
search time
• No brittle schema to
work around
• Automatically find
patterns and trends
13. Dashboards for Self-Service Analytics
Interactive Dashboards
and Charts
• Easy-to-use dashboard editor
• Chart overlay
• Pan and zoom
• In-dashboard drilldown
• Embed charts and
dashboards in 3rd party apps
• Reuse skills with Splunk
Enterprise and Hunk
15. MapR: Best Product, Best Business, Best Customers
15
Top Ranked Exponential Growth 500+ Customers Cloud Leaders
3X bookings Q1 ‘13 – Q1 ‘14
80% of accounts expand 3X
90% software licenses
<1% lifetime churn
>$1B in incremental revenue
generated by 1 customer
16. The Power of the Open Source CommunityManagement
MapR Data Platform
APACHE HADOOP AND OSS ECOSYSTEM
Security
YARN
Pig
Cascading
Spark
Batch
Spark
Streaming
Storm*
Streaming
HBase
Solr
NoSQL &
Search
Juju
Provisioning
&
coordination
Savannah*
Mahout
MLLib
ML, Graph
GraphX
MapReduce
v1 & v2
EXECUTION ENGINES DATA GOVERNANCE AND OPERATIONS
Workflow
& Data
Governance
Tez*
Accumulo*
Hive
Impala
Shark
Drill*
SQL
Sentry* Oozie ZooKeeperSqoop
Knox* WhirrFalcon*Flume
Data
Integration
& Access
HttpFS
Hue
* Certification/support planned for 2014
17. FOUNDATION
ArchitectureMatters for Success3
Data protection
& security
High performance
Multi-tenancy
Operational &
Analytical Workloads
Open standards
for integration
NEW APPLICATIONS SLAs TRUSTEDINFORMATION LOWERTCO
18. 18
Fraud Detection
• Zions Bank can predict
phishing behavior and
payments fraud in real time
and minimize their impact
Counterparty Risk
Management Analytics
• A large bank is able to
accurately understand the
aggregate risk associated with
all transactions with a specific
counterparty
MapR Customers in Financial Services
20. Getting Started
• Review the joint data sheet at
http://bit.ly/1oDYD3M
• Download the free sandboxes at
mapr.com/sandbox and
splunk.com/hunk
• Talk with us at .conf2014 or
Strata + Hadoop World NYC
Ineffective risk management is costly, in total dollar figures and as a percent of firm-wide profits. Shown here by the Swiss newspaper NZZ (in German) are fines ranging from $1.9 billion to $450 million. And the fine amounts dare rising. The JP Morgan Chase $13 billion settlement with the U.S. government regarding charges that the bank overstated the quality of mortgages it was selling to investors exceeds the total of these 12 fines combined.
Financial Services is one of the key industries where Splunk has had tremendous success. Leading Financial Services firms around the world are using Splunk every day to gain operational intelligence for their business. Here are some examples of how different companies are using Splunk to drive value.
Pause or stop Jobs in progress and revise queries interactively. We’re mindful of the resources we use in Hadoop.
Pause in Hunk: This pauses in the Search Head. Hadoop jobs keep running until the TCP header runs out. If you abandon a search for more than 30 seconds it will kill the search.
Hunk applies structure at search time
Designed for data exploration across large datasets – preview data & iterate quickly
No requirement to understand the data upfront
No limit to the number of results returned or the number of searches
No brittle schema to maintain or update
Find patterns and trends across disparate data sets in a “grab bag” Hadoop cluster
Use the Search Processing Language or create data models and pivot
Unlike Splunk Enterprise, Hunk applies schema for all fields – including transactions and localizations – at search time.
With interactive Dashboards and Charts, rapidly build custom dashboards with a new dashboard editor and deliver richer analytics experience with
MapR is the technology leader in Hadoop – the innovations in our distro enable us to use Hadoop not only to power analytic use cases such as what we’ll talk about with HP Vertica today, but also operational use cases such as real-time recommendation engines or fraud detection apps.
Our 500+ customers have had tremendous success in production with MapR, and we service many of the world’s largest organizations globally across 10 offices outside the US.
The power of MapR begins with the power of open source innovation and community participation.
In some cases MapR leads the community in projects like Apache Mahout (machine learning) or Apache Drill (SQL on Hadoop)
In other areas, MapR contributes, integrates Apache and other open source software (OSS) projects into the MapR distribution, delivering a more reliable and performant system with lower overall TCO and easier system management.
MapR releases a new version with the latest OSS innovations on a monthly basis. We add 2-4 new Apache projects annually as new projects become production ready and based on customer demand.
This analogy applies as well to building a data platform – you have to architect for the future. This allows you to build higher, stronger, and faster, without retrofitting later down the road (anyone who has added a second story to their house can attest to the additional cost and construction delays if you have to reinforce a foundation which wasn’t designed to hold the stress)
For business-critical applications you must have data protection and security (availability, data protection, and recovery), high performance (with random read-write system), multi-tenancy (to support multiple business units, isolate applications or user data,…), provide good resource and workload management to support multiple applications, and open standards to integrate with the rest of the enterprise data architecture
This data foundation allows you to support new data-driven applications (both operational and analytical) , maintain service level agreements with the business, provide information you can trust and count on being there when you need it, and ultimately being the best TCO for the long-run. Supporting enterprise systems without retrofits or multiple clusters to work around platform deficiencies (e.g., to support operational/online applications in Hadoop today, you need a separate HBase cluster – separate from the rest of your Hadoop cluster/investment)