the business data scientists their view of our world the
play

The Business Data Scientists Their View of Our World The Big Data - PowerPoint PPT Presentation

The Business Data Scientists Their View of Our World The Big Data Junk Yard Their View on our Happiness data scientist: 'the sexiest job of the 21st century' Their View on our work The BigData Junk Yard there will be too much data to handle,


  1. The Business Data Scientists

  2. Their View of Our World The Big Data Junk Yard

  3. Their View on our Happiness data scientist: 'the sexiest job of the 21st century'

  4. Their View on our work The BigData Junk Yard

  5. there will be too much data to handle, process or even “looked at” within any given budget and time constraints

  6. Lets’ start forgetting data DBMS Architects

  7. Lets’ start forgetting data DBMS Architects

  8. Data rotting The DBMS may selectively forget data on its own initiative for the sake of storage management and responsiveness.

  9. The food lifecycle refine rotting

  10. Lesson 1: Don't collect more Data than you can eat.

  11. Lesson 2: Purify and refine Data makes consumption pleasant and lasting

  12. Lesson 3: Data rotting is an evitable natural phenomena, learn to deal with Amnesia

  13. ......

  14. TAKE HOME MESSAGES • Database amnesia techniques is a barren research landscape • Prepare the end-users to cope with their dementing database • Providing medicines with clear cost/effectiveness • Re-asses all components of a DBMS to implement amnesia • Schema rotting • Query execution rotting • Index storage rotting • Record storage rotting • Operating system rotting, • Hardware rotting

  15. THANK YOU, ENJOY YOUR RESEARCH ADVENTURES

  16. Hardware rotting Hardware failures are a blessing, not a curse, as long as you can recognize them

  17. Operating System rotting The OOM killer on Linux kicks in when it is faced with an out-of-memory condition.

  18. Record rotting Tuples/pages/partitions that have not been accessed over a long period become the target for automated vacuum actions.

  19. Index rotting Index structures, such as hashes and B-trees, are automatically capped to consume less space at the cost of re-growing its branches

  20. Query rotting Every data item contributing to a query result set is removed and no derived object can be larger then the contribution set

  21. The medicine against rotting is to refine/purify

  22. Data fungi architecture

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend


More recommend