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Customer Use Case: How Arcadia Data works with Cloudera to bring On-Cluster Hadoop Visualization to business users

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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

  1. 1. 1© Cloudera, Inc. All rights reserved. Customer Use Case How Arcadia Data works with Cloudera to bring On- Cluster Hadoop Visualization to business users Headline Goes Here
  2. 2. 2© Cloudera, Inc. All rights reserved. Solution Overview Hadoop-native visualization platform that connects business 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 visualizing summaries
  3. 3. 3© Cloudera, Inc. All rights reserved. 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 Certification 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) Apache Sentry Yes Yes *CDH 5.8 Certification for Arcadia Enterprise 3.2 is under beta testing at Kaiser Permanente
  4. 4. 4© Cloudera, Inc. All rights reserved. The Customer • 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
  5. 5. 5© Cloudera, Inc. All rights reserved. CONSUMER PACKAGED GOODS (CPG) » CAMPAIGN EFFECTIVENESS » BRAND RECOGNITION » CUSTOMER BEHAVIOR DRIVE CUSTOMER INSIGHTS Improved Customer Insights from Digital Marketing campaigns intelligence Challenge: • Fragmented data infrastructure and silos of applications with product and brand information Solution: • Unified BI and Visual application for 100s of Brand Managers • High visibility into campaign effectiveness and brand recognition across geographies
  6. 6. 6© Cloudera, Inc. All rights reserved. Higher Product and service efficiencies from deeper market intelligence Challenge: • Lack of insights on how customers are reacting to marketing campaigns and how products are impacted Solution: • BI and Visual application that gathers intelligence on produce performance in relation to e-marketing campaigns • Enables brand managers to intelligently develop product roadmaps CONSUMER PACKAGED GOODS (CPG) » CUSTOMER INSIGHTS » MARKETING ANALYTICS » PRODUCT ROADMAP IMPROVE PRODUCT & SERVICES EFFICIENCY
  7. 7. 7© Cloudera, Inc. All rights reserved. Business Challenges • 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 Intervention needed!
  8. 8. 8© Cloudera, Inc. All rights reserved. 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 infrastructure. • 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.
  9. 9. 9© Cloudera, Inc. All rights reserved. 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
  10. 10. 10© Cloudera, Inc. All rights reserved. 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
  11. 11. 11© Cloudera, Inc. All rights reserved. Retail Store Geo Analysis YoY Growth metrics plotted by county for the chose sub-brand Trellising allows for quick trend analysis across multiple stores. Here showing store sales vs trade area sales to correlate potential shifts in buying pattern Choose a specific state to drill down to county level
  12. 12. 12© Cloudera, Inc. All rights reserved. Retail Stores drill down Interactive maps allows for easy visualization of spatial data zooming into details
  13. 13. 13© Cloudera, Inc. All rights reserved. Supply Chain Analysis Application Build stand-alone, fully native web applications with your organization logos & Develop your own analysis workflow with custom navigation Customize the application with your own business logic For example control what is shown based on action buttons Zoom into your data to better understand anomalies
  14. 14. 14© Cloudera, Inc. All rights reserved. Visual Data Modeling
  15. 15. 15© Cloudera, Inc. All rights reserved. Customer Behavior 5 5"

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