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Nov 13, 2017
How Arcadia Data works with Cloudera to bring On-Cluster Hadoop Visualization to business users
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Customer Use Case
How Arcadia Data works with Cloudera to bring On-
Cluster Hadoop Visualization to business users
Headline Goes Here
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users to big data
• Distributed BI & Analytics Engine
runs natively in Cloudera
• Visualize Historical & Real-time
data in a single platform
• Build data intelligent app
• Closed-loop navigation to
granular data, rather than just
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Arcadia - Cloudera Integration
• Arcadia Enterprise is a Cloudera Integrated Application
• Management : Cloudera Manager
• Security :
• Kerberos / LDAP / SSL Support
• Sentry support for Role Based Access. Roles imported from Sentry
• Historical Data : Impala
• Real-Time Data : Solr, Kudu
• Arcadia Data is a contributor to Apache Impala
Cloudera Version Product Version Interface Components Supports Kerberos Supports Sentry
CDH 5.5, 5.7, 5.8* Arcadia Enterprise 3.1, 3.2 Impala, Solr, Kudu, SparkSQL
Cloudera Manager (Parcel based)
*CDH 5.8 Certification for Arcadia Enterprise 3.2 is under beta testing at Kaiser Permanente
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• 179 Years old this year
• Countries of operation: ~70
• Countries where brands are sold: ~180
• Consumers served by our brands: 5 billion (approximate)
• Last FY Revenue: $76.28 billion
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» CAMPAIGN EFFECTIVENESS
» BRAND RECOGNITION
» CUSTOMER BEHAVIOR
Improved Customer Insights from Digital
Marketing campaigns intelligence
• Fragmented data infrastructure and
silos of applications with product and
• Unified BI and Visual application for
100s of Brand Managers
• High visibility into campaign
effectiveness and brand recognition
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Higher Product and service efficiencies
from deeper market intelligence
• Lack of insights on how customers are
reacting to marketing campaigns and
how products are impacted
• BI and Visual application that gathers
intelligence on produce performance in
relation to e-marketing campaigns
• Enables brand managers to intelligently
develop product roadmaps
» CUSTOMER INSIGHTS
» MARKETING ANALYTICS
» PRODUCT ROADMAP
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• Business teams needed access to more data ( sales, market measurements,
demographics, weather, social etc.) with more granularity to help drive deeper insights.
• Challenges delivering significantly better explanatory insight – “why is this happening”.
• Wanted to quickly acquire and integrate multiple structured and unstructured data
sources quickly, at volume.
• Needed the ability to be able to integrate a variety of NEW data types. Traditional
approaches not working.
• Growing data volumes = growing storage costs.
• Time to insight increasingly challenged
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Getting Started – Initial Assessment
• Concluded the Hadoop ecosystem was the right add.
• Buy vs. build: Customer saw no business value in building their own Hadoop
• Low cost storage option changes thinking at multiple levels.
• For speed, could deploy a preconfigured Hadoop appliance co-located with
their Data Warehouses, where the data was residing.
Cloudera + On-Cluster BI tool was a fit.
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Big Data – Example use-cases & business questions
1. Campaign analysis – understand online (web & mobile) campaigns across all brands.
a. Identify best and worst engaging campaigns to help drive executional learnings.
b. Segment reach to understand “Who” aspects of Brand targeting.
2. Retail sales analysis – combine retail & trade area sales to understand market
dynamics across geographies.
a. Does brand A have higher share in store than out, and how does that vary across stores of
that retailer? What correlates with that ?
b. Acceleration of sales – Is brand A accelerating in growth rate over time, and if so, is that
just in the store, just in the neighborhood, or both? What correlates with that?
3. Supply chain analysis – combine data from raw material suppliers with
manufacturing and customer shipments to get a detailed picture into supply chain
a. How have stock levels fluctuated over time in comparison to deliveries and raw supplies
b. Identify & measure non-productive inventory for manufacturing optimization
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Campaign Analysis Application
Understand high level metrics with the ability to drill
down to details
Augment analysis with a variety
of data types & sources such as
actual display ad images
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Retail Store Geo Analysis
metrics plotted by
county for the
Trellising allows for
quick trend analysis
across multiple stores.
Here showing store
sales vs trade area
sales to correlate
potential shifts in buying
Choose a specific
state to drill down to
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Retail Stores drill down
Interactive maps allows for
easy visualization of spatial
data zooming into details
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Supply Chain Analysis Application
Build stand-alone, fully native web applications with
your organization logos &
Develop your own analysis workflow with custom
Customize the application with your own
For example control what is shown
based on action buttons
Zoom into your data to better
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Visual Data Modeling
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