Month: May 2013
There will be live Wecast on June 12 (2013) on Introducing Java EE7. There will be some keynotes, some break out sessions that you can attend and you will have the opportunity to chat with some Java experts. The highlights of this event include:
- Business Keynote (Hasan Rizvi and Cameron Purdy)
- Technical Keynote (Linda DeMichiel)
- Breakout Sessions on different JSRs by specification leads
- Live Chat
- Lots of Demos
- Community, Partner, and Customer video testimonials
I joined a conference call on Thursday that was organised for members of the Oracle ACE program. This a full 1 hour conference call, presented by Arun Gupta. He spent the one hour call going through some of the new features coming in Java EE7
On 11th and 12th June we will be having our next SIG meetings for BI and Tech. The BI SIG will be on the 11th June in the Oracle offices in East Point. We then move the the Conrad Hotel on the 12th June for the Tech SIG. Here are the agendas for the 2 days.
These events are open to everyone, are free for members and a small fee for non-members.
To register for these event go to the following links
There are 2 PL/SQL packages for performing data mining/predictive analytics in Oracle. The main PL/SQL package is DBMS_DATA_MINING. This package allows you to build data mining models and to apply them to new data. But there is another PL/SQL package.
The DBMS_PREDICTIVE_ANALYTICS package is very different to the DBMS_DATA_MINING package. The DBMS_PREDICTIVE_ANALYTICS package includes routines for predictive analytics, an automated form of data mining. With predictive analytics, you do not need to be aware of model building or scoring. All mining activities are handled internally by the predictive analytics procedure.
Predictive analytics routines prepare the data, build a model, score the model, and return the results of model scoring. Before exiting, they delete the model and supporting objects.
The package comes with the following functions: EXPLAIN, PREDICT and PROFILE. To get some of details about these functions we can run the following in SQL.
This blog post will look at the EXPLAIN function.
EXPLAIN creates an attribute importance model. Attribute importance uses the Minimum Description Length algorithm to determine the relative importance of attributes in predicting a target value. EXPLAIN returns a list of attributes ranked in relative order of their impact on the prediction. This information is derived from the model details for the attribute importance model.
Attribute importance models are not scored against new data. They simply return information (model details) about the data you provide.
I’ve written two previous blog posts on Attribute Importance. One of these was on how to calculate Attribute Importance using the Oracle Data Miner tool. In the ODM tool it is now called Feature Selection and is part of the Filter Columns node and the Attribute Importance model is not persisted in the database. The second blog post was how you can create the Attribute Importance using the DBMS_DATA_MINING package.
EXPLAIN ranks attributes in order of influence in explaining a target column.
The syntax of the function is
data_table_name IN VARCHAR2,
explain_column_name IN VARCHAR2,
result_table_name IN VARCHAR2,
data_schema_name IN VARCHAR2 DEFAULT NULL);
data_table_name = Name of input table or view
explain_column_name = Name of column to be explained
result_table_name = Name of table where results are saved. It creates a new table in your schema.
data_schema_name = Name of schema where the input table or view resides. Default: the current schema.
So when calling the function you do not have to include the last parameter.
Using the same example what I have given in the previous blog posts (see about for the links to these) the following command can be run to generate the Attribute Importance.
data_table_name => ‘mining_data_build_v’,
explain_column_name => ‘affinity_card’,
result_table_name => ‘PA_EXPLAIN’);
One thing that stands out is that it is a bit slower to run than the DBMS_DATA_MINING method. On my laptop it took approx. twice to three time longer to run. But in total it was less than a minute.
To display the results,
The results are ranked in a 0 to 1 range. Any attribute that had a negative value are set to zero.
Oracle has build a number of formatting options into SQL Developer to allow you to output your data in some standard formats. This removes the need to use other tools or to write extra code or performs various follow up steps.
All you need to do is to add a comment and use the Scrip button
SELECT /*csv*/ * FROM scott.emp;
SELECT /*xml*/ * FROM scott.emp;
SELECT /*html*/ * FROM scott.emp;
SELECT /*delimited*/ * FROM scott.emp;
SELECT /*insert*/ * FROM SCOTT.EMP;
SELECT /*loader*/ * FROM scott.emp;
SELECT /*fixed*/ * FROM scott.emp;
SELECT /*text*/ * FROM scott.emp;
Hint: for some of these it is best to list the schema and table name in upper case
These are comments and not hints so they will not work in SQL*Plus.
The headline articles for the July/August 1999 edition of Oracle Magazine were focused on Business Intelligence and included topics on architectures, business plans, data integration, portals, dashboards, Oracle Express, data marts and data warehouses.
Other articles included:
- 15 Rules for Enterprise Portals
- Gear it to casual users
- Use intuitive classifications and searching
- Allow access to a publish/subscribe engine
- Enable universal connectivity to information resources
- Provide dynamic access to information resources
- Set up intelligent routing
- Integrate a business intelligence toolset
- Use a server based architecture
- Build in distributed, multithreaded services
- Enable flexible permission granting
- Append external interfaces
- Provide programmatic interfaces
- Establish internet security
- Make it cost effective to deploy
- Ensure that it can be customized and personalized
- Oracle Application Server release 4.0.8 was available for beta testing and includes support for Enterprise JavaBeans. Java Servlets, Java Server Pages and allows developers to build robust self service applications quickly
- Oracle and MapInfo joined forces to release an internet-based spatial-data analysis solution to help organizations to understand and visualize data and to identify patterns and customer trends
- Oracle makes available Oracle iTV platform, that is a solution that makes it possible for broadcast, cable and telecommunications providers to deliver interactive services .
- Nine tips for using Oracle Discover included:
- Us the decode statement
- Implement summary redirection
- create optional conditions (filters)
- use query statistics
- perform regular maintenance on the query statistics tables
- familiarize yourself with the EUL tables
- make regular backups
- modify registry settings
- delete objects with care
- Standardizing your interfaces. The first of a three part article on creating interfaces to the database. This article focused on showing how to setup and use UTL_FILE for loading data into and getting data out of the database.
- Creating a Virtual Private Database in Oracle 8i describes how to approach such a project to implement fine grained access control and gives the following steps for setting up a VPD
- create the application context
- create a package that sets the context
- create the policy function
- associate the policy function with a table or view
To view the cover page and the table of contents click on the image at the top of this post or click here.
My Oracle Magazine Collection can be found here. You will find links to my blog posts on previous editions and a PDF for the very first Oracle Magazine from June 1987.
Over the past couple of weeks I’ve come across the following articles, blog posts and discussions about Big Data and Analytics. There seems to be an underlying theme of ‘let’s get back to the core of the problem’ and big data is not that useful and only in certain cases.
As the Analytics 3.0 article indicates we should be concentrating on how we can use analytics to achieve a real goal for the organisation.
Most data sets are 40-60GB range – I can do that on my laptop, so that cannot be Big Data
It is also interesting to note that most of the people who have been working in the area for years (10+) are not believes in Big Data or they don’t even consider calling themselves Data Scientists.
The purpose of this post to to record these links in one place and to share with everyone else who might be interested.
Over the past 16 months (or so) I have give a join presentation with Anthony Heljula called ‘Getting Real Business Value from Oracle Data Mining and OBIEE’, at a number of conferences and OUG SIGs.
We have had a lot of very positive feedback on this presentation. The presentation is a busy 45 minutes (questions only at the end) that walks through a pilot data science project we did for a University in the UK.
We used Oracle Data Miner to build a predictive model that looks at student churn. We then integrated this Student Churn model into OBIEE Dashboards to illustrate how combining an Oracle Data Miner model into our data analysis we can gain a greater insight of our data.
We have submitted this presentation for Oracle Open World 2013 but we have renamed the title of the presentation to
“How UK Universities are using Oracle Data Science to protect their income”
If you are involved in presentation selection or know someone who is then maybe you might select this to be presented at OOW13 in September.
We submitted the presentation for OOW12 with not luck. So fingers crossed this time.