Kategoria BISAC: Computers >> Data Science - Data Analytics

The Oracle Utilities Pocket Reference is a handy, quick-reference guide to the multitude of Oracle utilities that database administrators (DBAs) use every hour of every day.As the undisputed leader among database products, Oracle is grasped conceptually by most DBAs. However, they understandably may not recall the specific utility to use for a given task, and, more commonly, won't in many cases remember the syntax to use. And that's exactly what the Oracle Utilities Pocket Reference supplies--the syntax and options for whatever utility a DBA needs to perform a given task.Some...

The Oracle database is one of the most popular in the world, and for good reason. It's compatible, scalable, portable, and capable of performing incredibly fast. The advantages Oracle holds over its competition come with a price, however--it's a highly complex database that's becoming more complex with every release. And this level of detail, of course, can begin to weigh on database administrators (DBAs).

Fortunately, the Oracle DBA Pocket Guide from O'Reilly is on the case. This handy reference is designed to help administrators make more effective use of their time by...

The Unix for Oracle DBAs Pocket Reference puts within easy reach the commands that Oracle database administrators need most when operating in a Unix environment. If you are an Oracle DBA moving to Unix from another environment such as Windows NT or IBM Mainframe, you know that these commands are far different from those covered in most beginning Unix books. To jump start your learning process, Don Burleson has gathered together in this succinct book the Unix commands he most often uses when managing Oracle databases. You'll be able to reach into your pocket for the answer when you...

Despite the excitement around "data science," "big data," and "analytics," the ambiguity of these terms has led to poor communication between data scientists and organizations seeking their help. In this report, authors Harlan Harris, Sean Murphy, and Marck Vaisman examine their survey of several hundred data science practitioners in mid-2012, when they asked respondents how they viewed their skills, careers, and experiences with prospective employers. The results are striking.

Based on the survey data, the authors found that data scientists today can be clustered into four...