By Sibanjan Das
Automate the predictive analytics approach utilizing Oracle info Miner and Oracle R firm. This publication talks approximately how either those applied sciences supplies a framework for in-database predictive analytics. you will see a unified structure and embedded workflow to automate a variety of analytics steps resembling facts preprocessing, version construction, and storing ultimate version output to tables.
You'll take a deep dive into numerous statistical types generic in companies and the way they are often computerized for predictive analytics utilizing quite a few SQL, PLSQL, ORE, ODM, and local R applications. you will get to grasp a number of thoughts to be had within the ODM workflow for using automation. additionally, you will get an figuring out of assorted how one can combine ODM programs, ORE, and local R programs utilizing PLSQL for automating the processes.
Data technological know-how Automation utilizing Oracle Data Miner and Oracle R Enterprise starts off with an advent to enterprise analytics, overlaying why automation is critical and the extent of complexity in automation at every one analytic level. Then, it makes a speciality of how predictive analytics will be computerized through the use of Oracle information Miner and Oracle R company. additionally, it explains whilst and why ODM and ORE are for use jointly for automation.
The next chapters aspect a number of statistical methods used for predictive analytics akin to calculating characteristic value, clustering tools, regression research, type innovations, ensemble versions, and neural networks. In those chapters additionally, you will get to appreciate the automation procedures for every of those statistical tactics utilizing ODM and ORE besides their program in a real-life company use case.
What you are going to learn
- Discover the performance of Oracle facts Miner and Oracle R Enterprise
- Gain easy methods to practice in-database predictive analytics
- Use Oracle's SQL and PLSQL APIs for construction analytical solutions
- Acquire wisdom of universal and widely-used enterprise statistical research techniques
Who this publication is for
- IT executives, BI architects, Oracle architects and builders, R clients and statisticians.
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Extra info for Data Science Using Oracle Data Miner and Oracle R Enterprise: Transform Your Business Systems into an Analytical Powerhouse
A SQL script eases the mundane task of manual configurations each and every time. For those who are not familiar with SQL scripts, SQL developer comes handy. SQL developer is an IDE (integrated development environment) for executing SQL and PLSQL scripts. Oracle Data Miner’s GUI and workflows are a part of it and can be easily configured from the SQL developer. 1. Creating a data mining user is the first step in configuring Oracle Data Miner. To start the configuration, open SQL Developer and follow these steps.
Optional: • Sample schemas for Oracle Database are installed. Some of the examples in this book use the tables/views of these schemas. Installation A data mining user and Data Miner repository are needed to start using Oracle Data Miner. This can be done using SQL scripts or from SQL developer GUI. A SQL script eases the mundane task of manual configurations each and every time. For those who are not familiar with SQL scripts, SQL developer comes handy. SQL developer is an IDE (integrated development environment) for executing SQL and PLSQL scripts.
Data Miner DMUSER connection 14. Select the plus (+) icon beside DMUSER, which will pop up a notification to install the Data Miner repository (Figure 2-14). Click Yes to continue Figure 2-14. Install the Data Miner repository 15. As SYS user has SYSDBA credentials, it can be used to install a data mining user. Enter the SYS credentials and continue with the installation (see Figure 2-15). 46 Chapter 2 ■ Installation and Hello World Figure 2-15. Enter SYS user and password screen 16. In the Repository Installation Settings, you have to choose the default tablespace and temporary tablespace for the ODMRSYS repository account (see Figure 2-16).