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[MongoDB.local Bengaluru 2018] The Path to Truly Understanding Your MongoDB Data
The document discusses the significance of data visualization in MongoDB, highlighting trends in analytics growth and methods for achieving effective data visualization. It outlines various architectures and tools for analytics, including MongoDB Compass, BI Connector, and MongoDB Charts, emphasizing their suitability for different user needs. A demo is proposed to illustrate the lifecycle of data handling from acquisition to sharing.
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Similar to [MongoDB.local Bengaluru 2018] The Path to Truly Understanding Your MongoDB Data
[MongoDB.local Bengaluru 2018] The Path to Truly Understanding Your MongoDB Data
- 1. #MDBlocal THE PATH TO TRULYUNDERSTANDING YOUR MONGODB DATA Bengaluru
- 2. #MDBlocal Vivek Singh Sr. SolutionArchitect, MongoDB
- 3. #MDBlocal AGENDA 1. Background 2. Theimportance of data visualization 3. Methods for data visualization in MongoDB 4. Demo
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- 6. #MDBlocal DATA GROWTH ISEXPLOSIVE • More data created in the last 2 years than entire previous history of the human race • By 2020: • 1.7MB per person every second
- 7. # M DB l o c a l • Analytics is big $! • $150B in 2017 • $210B+ in 2020 • Less than 0.5% of data is analysed and used – imagine the potential! THE STATE OF ANALYTICS Source: IDC. https://www.idc.com/getdoc.jsp?containerId=prUS42371417
- 8. #MDBlocal EVOLUTION OF ANALYTICS •Self service • Mobile access • Real time analytics • On-prem and cloud • On demand reporting 2018 Today2015 20162012 • Dedicated reporting team • Desktop access • Batch analytics • On prem only • Monthly reports
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- 11. #MDBlocal EARLY DATA VISUALIZATIONS CharlesMinard (1869) -- Napolean’s march and retreat on Moscow in 1812.
- 12. #MDBlocal SO YOU WANTTO VISUALIZE?
- 13. # M DB l o c a l EASY (ish) HARD (er?)
- 14. #MDBlocal • Use thecorrect architecture • Determine what your needs are • Multiple data sources? • Huge amounts of complex data? • Quick self service? • Choose the right solution for you THINGS TO THINK ABOUT
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- 16. # M DB l o c a l • Hidden secondaries maintain a copy of the primary’s data set • Hidden secondaries are used for workloads with different access patterns • Contain identical data, but can have different indexes • Hidden secondary cannot become primary ARCHITECTURE: HIDDEN REPLICAS OLTP Client Analytics Primary Secondary Secondary Secondary P=0 Hidden=true
- 17. # M DB l o c a l • An Extract-Transform-Load tool retrieves data from one or more databases, transforms the data and loads into a data warehouse • Minimal impact on OLTP systems; data can be highly optimised for analysis • Expensive to setup and maintain • Data can be stale ARCHITECTURE: ETL TO DATA WAREHOUSE Analytics DB1 DB2 DB3 Data Warehouse ETL OLTP Clients
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- 19. #MDBlocal BUILD YOUR OWN •Pro’s • Custom tailored solution: fits exactly as required! • Con’s • High investment • Maintenance • Deep understanding of the underlying tech and its language(s)
- 20. #MDBlocal USE THE TOOLSWE GIVE YOU
- 21. #MDBlocal MONGODB COMPASS • Developertool • Data management and manipulation • Interesting schema analysis • Used daily: a good first place to start
- 22. #MDBlocal WHEN TO USE •Day-to-day development/operations • Adding indexes • Viewing server stats • Data manipulation • 10,000->1ft view of data
- 23. #MDBlocal BI CONNECTOR • Visualizeand explore MongoDB data in SQL-based BI tools: • Automatically discovers the schema • Translates complex SQL statements issued by the BI tool into MongoDB aggregation queries • Converts the results into a tabular format for rendering inside the BI tool
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- 25. #MDBlocal WHEN TO USE •Multi datasources (not just mongodb) • Business analysts • Extremely powerful but high ramp
- 26. #MDBlocal MONGODB CHARTS • Lightweight •Intuitive • Build visualizations on MongoDB data (nested, polymorphic) • Share content in a dashboard
- 27. #MDBlocal WHEN TO USE •When you want quick answers • No need to flatten / ETL your mongodb data • Self service for the technical audience
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- 29. #MDBlocal LIFE CYCLE 1. Acquire2. Prep - Calcs - Groups - Data types 3. Visualize - Bar - Pie - Line 4. Explore - Dashboards 5. Share - Export - Collaborate - Embed
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