State of Data Last Week - #32

#analysis – How data can make you live forever – Scott Adams (@Dilbert) ponders if one could build a “smart analytical engine” that will learn and thrive on one’s online ‘persona’ data (email; tweets; blogs; comments; shopping; GPS) and once the person is dead can “represent” him/her in online communities and other digital places. One’s 23^rd generation could then have a “live chat” with forefather dead 1000 years ago!

Come to think of it, this probably makes more sense – and easier to do than – Cryogenics.

#architecture – NoSQL at Twitter, video presentation on Twitter’s choice and usage of NoSQL technologies – Cassandra, Hadoop, Redis etc.

#big_data – ‘Rumors of DBMS demise are greatly exaggerated’ (slides, if short on time)– IBM Distinguished Engineer Billy Newport discusses and contrasts the ‘SQL’ and ‘NoSQL mindsets’.

#DBMS – Database Administrator job requirement, probably written by a real Database Administrator – “Do you think the world should be solved through relational algebra? Don’t apply here. Have you edited a database redo/write-ahead log in a hex editor to bootstrap a failed recovery? Now we’re talking.”

#learning – A group of MIT researchers build a straw-man for DBaaS – Database-as-a-Service for cloud. The seminal paper analyzes cost and impact of multi-tenancy, elastic scale, privacy, partitioning and migration in cloud-based database.

#visualization – Mint does a simple visualization showing what Credit Card number digits mean.

 

#etc

 

• ‘Say Cheese’ – Intel and Kraft could scan your face and predict what you want to eat. Spooky video analytics at Dinner table!
• What’s in a Zname – (via Freakonomics) ‘people with last names toward the end of the alphabet are faster at making buying decisions. Why? Kids with the A to I last names were always first in line, whereas kids with last names from R to Z got sidelined when quantities were limited, or just grew to hate waiting in line’
• Does Users- per- Employee Ratio matter more than Revenue-per-employee? Mozilla has 1.6M users per employee; Twitter 60K per employee; WikiMedia – whew – 7.2M users per employee.
• Commenting SQL code is not only a good practice, comments could also improve SQL performance. What?? No, really – here is a use case. It’s a trick, read on the comments if the rationale bothers you.

 

About these ads