I am not sure apeescape’s ggplot2 area plot with intensity colouring is really the best way of presenting the information, but it had me intrigued enough to replicate it using base R graphics.
We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is scary.
We have a mild obsession with employee productivity and how that declines as companies get bigger. We have previously found that when you treble the number of workers, you halve their individual productivity which is mildly scary.
Following on from my previous post about improving performance of R by linking with optimized linear algebra libraries, I thought it would be useful to try out the five benchmarks Revolutions Analytics have on their Revolutionary Performance pages.
Can we make our analysis using the R statistical computing and analysis platform run faster? Usually the answer is yes, and the best way is to improve your algorithm and variable selection.
I needed a fast way of eliminating observed values with zero variance from large data sets using the R statistical computing and analysis platform. In other words, I want to find the columns in a data frame that has zero variance. And as fast as possible, because my data sets are large, many, and changing fast. The final result surprised me a little.
We knew the potential existed already, of course. Mobile devices in the USA generates some 600 billion transactions per day, each tagged with the location and time. Jeff Jonas says,
Every call, text message, email and data transfer handled by your mobile device creates a transaction with your space-time coordinate[…]. Got a Blackberry? Every few minutes, it sends a heartbeat, creating a transaction whether you are using the phone or not. That is some 7 million transactions per second, on average.
This is by far the best description of why traditional parallel databases (like Teradata, Greenplum et al.) is a evolutionary dead end. But much more than a theoretical discussion, they have built a solution which they call HadoopDB. It is based on Hadoop, PostgreSQL, and Hive and is completely Open Source. Alternative, column-based, backends to PostgreSQL are being implemented now. Read: Announcing release of HadoopDB.
The nice people at Velocity has released The B2B Content Marketing Workbook. It is behind a registration wall which means we wouldn’t normally recommend it but you can just type junk in the fields if you are not comfortable with giving your personal details to a marketing agency. (Think about it….) If you are relatively new in the B2B world, say having joined a professional services or consulting organization, you may find this one useful.