sisense and simba mongodb analytics webinar
TRANSCRIPT
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Simba ConnectsDe 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 standardsODBC 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
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Customers who license & shipSimba's connectivity with their products
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A few of our customers who useSimba MongoDB drivers
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Customer Feedback
It just works!..Automatic
schema generationworks great...
I don't need to know MongoDB query language!
Great compatibilitywith my <BI tool>...
Really good performanceeven on a laptop
Gets the job done
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Simba's Data Connectivity Drivers & SDKs
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Thank you.www.simba.com
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From Operations to Insights
with MongoDB
Speaker: Evan Castle, Product Manager
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→ The Analytical Challenges of MongoDB
→ Example: Customer Use Case for MongoDB
→ Example: Sisense Analytics Driven by MongoDB
Agenda
→ Advantages of Sisense and MongoDB
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• 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
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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
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• 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
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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
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Customer Use Case for MongoDB
• Reduce time to insight
• Work Flow Automation
• Scale New Services
• Managed by business
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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
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Thank you