Free database cloud e-book from Oracle

Building a Database in the Cloud? E-Book Explains How.

It’s free for download as long as you have a free Oracle account.

Clear and concise, practical, filled with time-saving tips—the reviews are in on Building a Database Cloud for Dummies.

This quick-reference guide, organized into six short chapters and supplemented with helpful illustrations, provides a clear overview of the cloud and step-by-step instructions on deploying database as a service. Download the complimentary e-book today and learn how to:

  • Build a vision and business case for the cloud
  • Operate and deploy a database in the private cloud
  • Maximize success, with a list of the top 10 things to consider when starting

Database clouds allow businesses to drive down costs while increasing business agility and IT performance. See for yourself how to save money, simplify management, and improve resource efficiency with a database cloud.

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A beer recommendation system made with R

This neat little app is the product of a recommendation system built using the R language by the folks behind the yhat blog. It’s based on about 1.5 million beer reviews from the Beer Advocate. The ratings were read into a Postgres database and then imported to R using the RPostgreSQL package. From there, you can easily make a start at collaborative filtering in R by using the intersect function to identify all reviewers that have rated a particular pair of beers, and write a distance function in R to measure how close the two beers are according to the reviewers’ ratings. Do this for all pairs of beers (using a neat application of the expand.grid function), put the results behind a JavaScript UI, and you’ve got yourself a beer recommender. (This is similar to the approach used for this recommendation engine for movies.)

 

You don’t need Big Data. You need Analytics!

Readers Write: Health Data Analytics Provides Greater Value Over Big Data

The article provides the following six items to consider for analytics, in spite of the Big Data hype. They are quite useful and provides very valuable insight.

  1. Ignore the hype.
  2. Be realistic.
  3. Conduct an in-depth assessment.
  4. Start small.
  5. Grow intelligently.
  6. Focus on your people.