Concur Discovers the True Value of Data
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Concur, the leading provider of spend management solutions and services, will be joining us to discuss how they implemented Cloudera for data discovery and analytics. Using an enterprise data hub, Concur was able to provide their data scientists a centralized environment that allowed for faster and smarter analytic development. During this session you will learn about: The end user process of building smarter analytics and how Cloudera can help Concurs pre-Hadoop and post-Hadoop environment Summary of key lessons and end benefits of Concur’s modern architecture Denny Lee: Sr. Director, Data Sciences Engineering Denny is a hands on data architect and developer / hacker with more than 15 years of experience developing internet-scale infrastructure, data platforms, and distributed systems for both On-Premises and Cloud. His key focus surround solving complex large scale data problems - providing not only architectural direction but hands-on implementation of these systems to facilitate a successful data discovery and analytic environment.
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Concur Discovers the True Value of Data
- 1. 1© Cloudera, Inc. All rights reserved. Concur Discovers the True Value of Data
- 2. 2© Cloudera, Inc. All rights reserved. Agenda Data Discovery & Analytics Overview Concur – Before, After, and Key Lessons Learned Live Q&A SPEAKERS TJ Laher Product Marketing at Cloudera Denny Lee Sr. Director, Data Science Engineering at Concur tjlaher dennylee
- 3. 3© Cloudera, Inc. All rights reserved. Objectives of Data Discovery & Analytics Report Model Rule Marketing analysis Log analysis Churn analysis Product recommendation Predictive support Trade recommendation Ad targeting Transaction classification Lead scoring
- 4. 4© Cloudera, Inc. All rights reserved. It’s an Iterative Process Report, Model, or Rules Ingest Transformation 80% of Time Diverse Ingest Search and lineage Agile Transforms 20% of Time SQL Statistical Machine Learning Implement Point Solution Custom App Analysis Technique Access Data Generation Data Discovery & Analytics Flow
- 5. 5© Cloudera, Inc. All rights reserved. A Traditional Architecture Access Data Experiment FastAnalyze Data Enterprise Data Warehouse ImplementData Sources ETL Structured Unstructured Ingest Storage #1, 2, N ELT Store & Process Traditional Architecture EDW Archive ETL Access Data Analyze Data Search Statistical Machine Learning SQL Serve Serve Serve Optimize Implement Custom Application Point Solution ELT ELT
- 6. 6© Cloudera, Inc. All rights reserved. Challenges with Traditional Architectures Enterprise Data Warehouse ImplementData Sources ETL Structured Unstructured Ingest Storage #1, 2, N ELT Store & Process Traditional Architecture EDW Archive ETL Access Data Analyze Data Search Statistical Machine Learning SQL Serve Serve Serve Optimize Implement Custom Application Point Solution ELT ELT 1) Limited Data 2) Long Time to Value 1 2 2 3 3 3) Compliance & Privacy Concerns 3
- 7. 7© Cloudera, Inc. All rights reserved. A New Way Forward 1) Unlimited Data Access 2) Reduce Time to Value 3) Secure and Compliant Enterprise Data Warehouse ImplementData Sources Structured Unstructured ELT Store & Process Modern Architecture EDW ETL Access Data Analyze Data Statistical Machine Learning SQL Serve Optimize Implement Custom Application Point Solution ETL Active Ingest Ingest EDH Archiv e Load Cloudera Search ELT 3 2 3 1 1
- 8. 8© Cloudera, Inc. All rights reserved. Concur Data Discovery & Analytics
- 9. 9© Cloudera, Inc. All rights reserved. About Concur What do we do - Global customer base of 20,000 clients and 25 million users Processing more than $50 Billion in Travel & Expense (T&E) spend each year Who is Concur - Leading provider of spend management solutions and (Travel, Invoice, TripIt, etc.) services in the world
- 10. 10© Cloudera, Inc. All rights reserved. Our Objectives Deeper BI Reports Starbucks Store #3313 601 108th Ave NE Bellevue, WA (425) 646-9602 ------------------------------- Chk 713452 05/14/2014 11:04 AM 1961558 Drawer: 1 Reg: 1 ------------------------------- Bacon Art Brkfst 3.45 Warmed T1 Latte 2.70 Triple 1.50 Soy 0.60 Gr Vanilla Mac 4.15 Reload Card 50.00 AMEX $50.00 XXXXXXXXXXXXXXXXXX1004 SBUX Card $13.56 SUBTOTAL $62.40 New Caffe Espresso Frappuccino(R) Blended beverage Our Signature Frappuccino(R) roast coffee and fresh milk, blended with ice. Topped with our new espresso whipped cream and new Italian roast drizzle Better Classifications Smarter Predictions
- 11. 11© Cloudera, Inc. All rights reserved. The Pre-Hadoop Environment Travel Invoice Expense 1 Difficult to connect to multiple sources 1 BI Challenges
- 12. 12© Cloudera, Inc. All rights reserved. The Pre-Hadoop Environment Travel Invoice Expense 1 2 Difficult to connect to multiple sources Couldn’t analyze new data sources BTS Google Analytics Weather 1 2 BI Challenges
- 13. 13© Cloudera, Inc. All rights reserved. The Pre-Hadoop Environment Travel Invoice Expense 1 2 3 Difficult to connect to multiple sources Couldn’t analyze new data sources Challenges BTS Google Analytics Weather Advanced analytics was a dream 1 2 BI Advanced Analytics 3
- 14. 14© Cloudera, Inc. All rights reserved. Concur’s Modern Hadoop Architecture Complete data access (structured and unstructured) 1 Improvements New Data Pig Process 1 1 Store HDFS
- 15. 15© Cloudera, Inc. All rights reserved. Concur’s Modern Hadoop Architecture Complete data access (structured and unstructured) 1 Large scale ad-hoc queries2 Pig Process 1 1 Store HDFS HUE Discover Impala Solr Access BI 2 HiveImprovements New Data
- 16. 16© Cloudera, Inc. All rights reserved. Concur’s Modern Hadoop Architecture Complete data access (structured and unstructured) Quick Iterations for advanced analytics 3 1 Large scale ad-hoc queries2 Pig Process HUE Model R MLlib 1 1 Discover Impala Solr Spark Access BI Store HDFS 2 3 HiveImprovements New Data
- 17. 17© Cloudera, Inc. All rights reserved. The Modern Analyst Flow Find Data Prepare Data Analyze Data
- 18. 18© Cloudera, Inc. All rights reserved. Business and Technical ROI Technology ROI Business ROI Customer 360 view leading to better experience Insight into customer travel, expenses, and T&E Single platform for emerging advanced use cases Merge together storage systems for simpler management Unified access to disparate data Scale affordably
- 19. 19© Cloudera, Inc. All rights reserved. Key Leanings Crawl, walk, run It takes time, start now Lean on experts in the community It is a cultural shift as much as a technology shift
- 20. 20© Cloudera, Inc. All rights reserved. Q&A
- 21. 21© Cloudera, Inc. All rights reserved. Thank you
Editor's Notes
- Pulling from the “Insights Section”
- Why Hadoop slide content: Even with primarily relational systems, it involved hundreds of sources Getting a BI tool to connect to so many sources is … not fun More times than not, we needed to understand a subset or aggregate of this data - not all of the data! Can use Pig to process, extract, filter the data Can use Hive - a SQL like query language - to query my data
- Why Hadoop slide content: Even with primarily relational systems, it involved hundreds of sources Getting any BI tool to connect to so many sources is … not fun More times than not, we needed to understand a subset or aggregate of this data - not all of the data! Can use Pig to process, extract, filter the data Can use Hive - a SQL like query language - to query my data
- Why Hadoop slide content: Even with primarily relational systems, it involved hundreds of sources Getting any BI tool to connect to so many sources is … not fun More times than not, we needed to understand a subset or aggregate of this data - not all of the data! Can use Pig to process, extract, filter the data Can use Hive - a SQL like query language - to query my data