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Sisense and Simba MongoDB Analytics Webinar

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In this joint webinar between Sisense and Simba you will learn how to access, prepare and analyze data in MongoDB using Sisense BI. Sisense Product Manager Evan Castle goes over a sample automated analytics workflow for MongoDB leveraging Simba ODBC connectivity, schema auto-discovery and customization. You can watch the video recording at http://www.simba.com/webinar/operations-insights-mongodb-sisense-simba-odbc/

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Sisense and Simba MongoDB Analytics Webinar

  1. 1. Simba Connects De facto standard connectivity for major Hadoop distributions, leading NoSQL & BI tools Co-created original ODBC specification with Microsoft Shipped the first ODBC driver for Hadoop Hive Compliance with SQL-92 & the latest data connectivity standards ODBC 3.8 & JDBC 4.2 Collaborative Query Execution, fastest performance & advanced deployment options Automatic schema discovery and re-normalization Support for engineers by engineers Widest platform support, including Windows, Mac, Linux, Un*x & iOS
  2. 2. Customers who license & ship Simba's connectivity with their products
  3. 3. A few of our customers who use Simba MongoDB drivers
  4. 4. Customer Feedback It just works!.. Automatic schema generation works great... I don't need to know MongoDB query language! Great compatibility with my <BI tool>... Really good performance even on a laptop Gets the job done
  5. 5. Simba's Data Connectivity Drivers & SDKs
  6. 6. Thank you. www.simba.com Coming up next a presentation by Evan Castle, Sisense Product Manager ↓
  7. 7. From Operations to Insights with MongoDB Speaker: Evan Castle, Product Manager
  8. 8. → The Analytical Challenges of MongoDB → Example: Customer Use Case for MongoDB → Example: Sisense Analytics Driven by MongoDB Agenda → Advantages of Sisense and MongoDB
  9. 9. • Unstructured schemas are poor for analytics • Difficult to mashup different data sources • MongoDB is a technical environment, how do you leverage existing skillsets to analyze MongoDB • Not scalable for analytics purposes The Analytical Challenges of MongoDB
  10. 10. Operational Data vs. Analytical Data MongoDB Operational Benefits Sisense Analytical Benefits Dynamic Schema Robust Renormalization Easy for Programmers Easy for Analysts Many Attributes Support Many Attributes Horizontal Scaling Support Big Data
  11. 11. • SQL on NoSQL • ETL and Easy Visualization • Mashup Multiple Sources • Fast Columnar Data Store • Complex data Immediate query results • SSL Support • Intelligent Renormalization • Performance – aggregation, buffering, batching Advantages of Sisense on MongoDB
  12. 12. 360 Degree View Of Mongodb And All Business Data • Central location • Multiple Sources • Support complex columnar models Automatic, Visualized Insight for Everyone • ETL for business • High performance on large complex data sets • Visual front end Sisense Analytics Driven by MongoDB
  13. 13. Customer Use Case for MongoDB • Reduce time to insight • Work Flow Automation • Scale New Services • Managed by business
  14. 14. Demo Auto detection Auto or opportunity to make schema changes Virtual Tables Auto or opportunity to make schema changes Columnar Solution Sisense offers the ability to analyze data with many columns like MongoDB Mashup Drag and Drop mashup Interactive Dashboards Anyone can answer complex business questions
  15. 15. Thank you

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