The latest edition of Oracle Magazine is now available online and can be viewed at http://www.oracle.com/technetwork/oramag/magazine/current-issue/index.html
I’ve been included in the Peer-to-Peer feature, along with two other Oracle ACEs. The Peer-to-Peer feature is a regular part in Oracle Magazine and typically gives a short profile of 3 Oracle ACEs or ACE Directors.
If you have subscribed to get a printed copy, we should be getting a copy of it in the post over the next couple of weeks.
Here are the links to the 2 different sets of Big Data videos that Oracle have produced over the past 12 months
Oracle Big Data Videos - Version 1
Episode 2 - Gold Mine or Just Stuff
Episode 4 - Everything You Always Wanted to Know
Oracle Big Data Videos - Version 2
Episode 1 - Overview for the Boss
Episode 3 - Acquiring Big Data
Episode 4 - Organising Big Data
Episode 5 - Analysing Big Data
Other videos include
The headline articles for the November/December 1996 edition of Oracle Magazine were focused on VLDB with articles on scaling to petabyte sized databases, the latest and best hardware to use, what new exist features in 7.3 and 8 for VLDBS, what new tools exists to assist administrators with the scale of the database.
Other articles included:
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.
Calling all Oracle users in Ireland.
Tom Kyte will be back in Dublin on Wednesday 19th September for a half day seminar.
The event is is being organised by the Ireland OUG and Oracle.
It will be in the Gibson Hotel beside the Point village.
This is a FREE event for everyone, so share the news and get to see Tom Kyte present for a 4 hours.
As they say spaces are limited, so book your place today. I have.
To register for the event – click here.
The call for papers is now open for Oracle technical papers for publication in the UKOUG Oracle Scene magazine.
The submission date for completed papers is 24th August.
To get more information of paper guidelines and submission details go to,
http://www.ukoug.org/what-we-offer/oracle-scene/
The Winter edition will be published online and in print format around the end of October. This will be in time for the EPM & Hyperion, JDE and UKOUG 2012 conferences. So this is a chance to get your message across to these communities.
Did you get a presentation accepted for the UKOUG annual conference or were you disappointed ? Maybe you could consider writing a paper based on your presentation and submit it for consideration.
How about advertising in Oracle Scene. Over the past couple of editions we have had a significant increase in readership, with readership from countries around the world.
Over the past few years Oracle Scene has moved from being a regional User Group magazine to having a readership in 30+ countries around the world.
Why am I writing this post ? I’m a deputy editor of Oracle Scene
The headline articles for the September/October 1996 edition of Oracle Magazine was on Putting the Web to Work and focused how to build web based applications. Topics covered included the Web Server, Intranet vs Client/Server applications, what (Oracle) tools to use.
Oracle articles included:
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.
Calling all Oracle users in Ireland.
Oracle is hosting a Technology day in Dublin on Thursday 15th November. This one day event will be held in the Croke Park Conference Centre.
They will be talking about Cloud Computing, Mobile Computing, Social Media and Big Data.
They are also hoping to include some of the updates and product news that will be announced at Oracle Open World in early October.
As this is not an Oracle User Group event, you should expect a certain amount of marketing and sales pitches at this event.
To register for this event got to – Register Now
The headline articles for the July/August1996 edition of Oracle Magazine was on how to balance security and communication in a distributed world, extending Oracle power objects applications and automating Oracle tuning
Oracle articles included:
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.
The content catalog for Oracle Open World 2012 was made public during the week. OOW is on between 30th September and 4th October.
The following table gives a list of most of the Data Analytics type sessions that are currently scheduled.
Why did I pick these sessions? If I was able to go to OOW then these are the sessions I would like to attend. Yes there would be many more sessions I would like to attend on the core DB technology and Development streams.
| Session Title | Presenters |
| CON6640 - Database Data Mining: Practical Enterprise R and Oracle Advanced Analytics | Husnu Sensoy |
| CON8688 - Customer Perspectives: Oracle Data Integrator | Gurcan Orhan - Software Architect & Senior Developer, Turkcell Technology R&D Julien Testut - Product Manager, Oracle |
| HOL10089 - Oracle Big Data Analytics and R | George Lumpkin - Vice President, Product Management, Oracle |
| CON8655 - Tackling Big Data Analytics with Oracle Data Integrator | Mala Narasimharajan - Senior Product Marketing Manager, Oracle Michael Eisterer - Principal Product Manager, Oracle |
| CON8436 - Data Warehousing and Big Data with the Latest Generation of Database Technology | George Lumpkin - Vice President, Product Management, Oracle |
| CON8424 - Oracle’s Big Data Platform: Settling the Debate | Martin Gubar - Director, Oracle Kuassi Mensah - Director Product Management, Oracle |
| CON8423 - Finding Gold in Your Data Warehouse: Oracle Advanced Analytics | Charles Berger - Senior Director, Product Management, Data Mining and Advanced Analytics, Oracle |
| CON8764 - Analytics for Oracle Fusion Applications: Overview and Strategy | Florian Schouten - Senior Director, Product Management/Strategy, Oracle |
| CON8330 - Implementing Big Data Solutions: From Theory to Practice | Josef Pugh - , Oracle |
| CON8524 - Oracle TimesTen In-Memory Database for Oracle Exalytics: Overview | Tirthankar Lahiri - Senior Director, Oracle |
| CON9510 - Oracle BI Analytics and Reporting: Where to Start? | Mauricio Alvarado - Principal Product Manager, Oracle |
| CON8438 - Scalable Statistics and Advanced Analytics: Using R in the Enterprise | Marcos Arancibia Coddou - Product Manager, Oracle Advanced Analytics, Oracle |
| CON4951 - Southwestern Energy’s Creation of the Analytical Enterprise | Jim Vick - , Southwestern Energy Richard Solari - Specialist Leader, Deloitte Consulting LLP |
| CON8311 - Mining Big Data with Semantic Web Technology: Discovering What You Didn’t Know | Zhe Wu - Consultant Member of Tech Staff, Oracle Xavier Lopez - Director, Product Management, Oracle |
| CON8428 - Analyze This! Analytical Power in SQL, More Than You Ever Dreamt Of | Hermann Baer - Director Product Management, Oracle Andrew Witkowski - Architect, Oracle |
| CON6143 - Big Data in Financial Services: Technologies, Use Cases, and Implications | Omer Trajman - , Cloudera Ambreesh Khanna - Industry Vice President, Oracle Sunil Mathew - Senior Director, Financial Services Industry Technology, Oracle |
| CON8425 - Big Data: The Big Story | Jean-Pierre Dijcks - Sr. Principal Product Manager, Oracle |
| CON10327 - Recommendations in R: Scaling from Small to Big Data | Mark Hornick - Senior Manager, Oracle |
In previous post I gave the details of how you can use Regression in Oracle Data Miner to predict/forecast the lean of the tower in future years. This was based on building a regression model in ODM using the known lean/tilt of the tower for a range of years.
In this post I will show you how you can do the same tasks using the Oracle Data Miner functions in SQL and PL/SQL.
Step 1 – Create the table and data
The easiest way to do this is to make a copy of the PISA table we created in the previous blog post. If you haven’t completed this, then go to the blog post and complete step 1 and step 2.
create table PISA_2
as select * from PISA;
Step 2 – Create the ODM Settings table
We need to create a ‘settings’ table before we can use the ODM API’s in PL/SQL. The purpose of this table is to store all the configuration parameters needed for the algorithm to work. In our case we only need to set two parameters.
BEGIN
delete from pisa_2_settings;
INSERT INTO PISA_2_settings (setting_name, setting_value) VALUES
(dbms_data_mining.algo_name, dbms_data_mining.ALGO_GENERALIZED_LINEAR_MODEL);
INSERT INTO PISA_2_settings (setting_name, setting_value) VALUES
(dbms_data_mining.prep_auto,dbms_data_mining.prep_auto_off );
COMMIT;
END;
Step 3 – Build the Regression Model
To build the regression model we need to use the CREATE_MODEL function that is part of the DBMS_DATA_MINING package. When calling this function we need to pass in the name of the model, the algorithm to use, the source data, the setting table and the target column we are interested in.
BEGIN
DBMS_DATA_MINING.CREATE_MODEL(
model_name => 'PISA_REG_2',
mining_function => dbms_data_mining.regression,
data_table_name => 'pisa_2_build_v',
case_id_column_name => null,
target_column_name => 'tilt',
settings_table_name => 'pisa_2_settings');
END;
After this we should have our regression model.
Step 4 – Query the Regression Model details
To find out what was produced as in the previous step we can query the data dictionary.
SELECT model_name,
mining_function,
algorithm,
build_duration,
model_size
from USER_MINING_MODELS
where model_name like 'P%';
select setting_name,
setting_value,
setting_type
from all_mining_model_settings
where model_name like 'P%';
Step 5 – Apply the Regression Model to new data
Our final step would be to apply it to our new data i.e. the years that we want to know what the lean/tilt would be.
SELECT year_measured, prediction(pisa_reg_2 using *)
FROM pisa_2_apply_v;
This blog post will look at how you can use the Regression feature in Oracle Data Miner (ODM) to predict the lean/tilt of the Leaning Tower of Pisa in the future.
This is a well know regression exercise, and it typically comes with a set of know values and the year for these values. There are lots of websites that contain the details of the problem. A summary of it is:
The following table gives measurements for the years 1975-1985 of the "lean" of the Leaning Tower of Pisa. The variable "lean" represents the difference between where a point on the tower would be if the tower were straight and where it actually is. The data is coded as tenths of a millimetre in excess of 2.9 meters, so that the 1975 lean, which was 2.9642.
Given the lean for the years 1975 to 1985, can you calculate the lean for a future date like 200, 2009, 2012.
Step 1 – Create the table
Connect to a schema that you have setup for use with Oracle Data Miner. Create a table (PISA) with 2 attributes, YEAR_MEASURED and TILT. Both of these attributes need to have the datatype of NUMBER, as ODM will ignore any of the attributes if they are a VARCHAR or you might get an error.
CREATE TABLE PISA
(
YEAR_MEASURED NUMBER(4,0),
TILT NUMBER(9,4)
);
Step 2 – Insert the data
There are 2 sets of data that need to be inserted into this table. The first is the data from 1975 to 1985 with the known values of the lean/tilt of the tower. The second set of data is the future years where we do not know the lean/tilt and we want ODM to calculate the value based on the Regression model we want to create.
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1975,2.9642);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1976,2.9644);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1977,2.9656);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1978,2.9667);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1979,2.9673);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1980,2.9688);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1981,2.9696);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1982,2.9698);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1983,2.9713);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1984,2.9717);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1985,2.9725);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1986,2.9742);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1987,2.9757);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1988,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1989,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1990,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (1995,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (2000,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (2005,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (2010,null);
Insert into DMUSER.PISA (YEAR_MEASURED,TILT) values (2009,null);
Step 3 – Start ODM and Prepare the data
Open SQL Developer and open the ODM Connections tab. Connect to the schema that you have created the PISA table in. Create a new Project or use an existing one and create a new Workflow for your PISA ODM work.
Create a Data Source node in the workspace and assign the PISA table to it. You can select all the attributes..
The table contains the data that we need to build our regression model (our training data set) and the data that we will use for predicting the future lean/tilt (our apply data set).
We need to apply a filter to the PISA data source to only look at the training data set. Select the Filter Rows node and drag it to the workspace. Connect the PISA data source to the Filter Rows note. Double click on the Filter Row node and select the Expression Builder icon. Create the where clause to select only the rows where we know the lean/tilt.
Step 4 – Create the Regression model
Select the Regression Node from the Models component palette and drop it onto your workspace. Connect the Filter Rows node to the Regression Build Node.
Double click on the Regression Build node and set the Target to the TILT variable. You can leave the Case ID at <None>. You can also select if you want to build a GLM or SVM regression model or both of them. Set the AUTO check box to unchecked. By doing this Oracle will not try to do any data processing or attribute elimination.
You are now ready to create your regression models.
To do this right click the Regression Build node and select Run. When everything is finished you will get a little green tick on the top right hand corner of each node.
Step 5 – Predict the Lean/Tilt for future years
The PISA table that we used above, also contains our apply data set
We need to create a new Filter Rows node on our workspace. This will be used to only look at the rows in PISA where TILT is null. Connect the PISA data source node to the new filter node and edit the expression builder.
Next we need to create the Apply Node. This allows us to run the Regression model(s) against our Apply data set. Connect the second Filter Rows node to the Apply Node and the Regression Build node to the Apply Node.
Double click on the Apply Node. Under the Apply Columns we can see that we will have 4 attributes created in the output. 3 of these attributes will be for the GLM model and 1 will be for the SVM model.
Click on the Data Columns tab and edit the data columns so that we get the YEAR_MEASURED attribute to appear in the final output.
Now run the Apply node by right clicking on it and selecting Run.
Step 6 – Viewing the results
Where we get the little green tick on the Apply node we know that everything has run and completed successfully.
To view the predictions right click on the Apply Node and select View Data from the menu.
We can see the the GLM mode gives the results we would expect but the SVM does not.
