Mark Townsend, Database Product Manager at Oracle gave a presentation on Big Data at the UKOUG conference and used the following videos to illustrate how a company can evolve their Big Data into useful and meaningful information.
Big Data – Gold Mine or just Stuff
On Wednesday 7th Dec I gave my presentation at the UKOUG conference in Birmingham. The main topic of the presentation was on using the Oracle Data Miner PL/SQL API to implement a model in a production environment.
There was a good turn out considering it was the afternoon of the last day of the conference.
I asked the attendees about their experience of using the current and previous versions of the Oracle Data Mining tool. Only one of the attendees had used the pre 11g R2 version of the tool.
From my discussions with the attendees, it looks like they would have preferred an introduction/overview type presentation of the new ODM tool. I had submitted a presentation on this, but sadly it was not accepted. Not enough people had voted for it.
For for next year, I will submit an introduction/overview presentation again, but I need more people to vote for it. So watch out for the vote stage next June and vote of it.
Here are the links to the presentation and the demo scripts (which I didn’t get time to run)
Demo Script 1 – Exploring and Exporting model
Demo Script 2 – Import, Dropping and Renaming the model. Plus Queries that use the model
Today (Monday 5th Dec) is the first day of the UKOUG Conference in Birmingham.
Tonight we have the Focus Pubs session starting at 8:45pm. This year we have a Ireland table for all of the Irish people at the conference to gather at and to meet.
I’ll be there so drop along and say hello.
At 5:20pm today (Friday 2nd December), I received an email from the Oracle ACE program. I had been nominated for the award of Oracle ACE.
“You have been chosen based on your significant contribution and activity in the Oracle technical community. Like your fellow Oracle ACEs, you have demonstrated a proficiency in Oracle technology as well as a willingness to share your knowledge and experiences with the community.”
I am so honoured, considering the experts from around the world that are members of the Oracle ACE program.
The Oracle ACE Award is issued by the Oracle Corporation and the award is made to people who are know for their strong credentials in the Oracle community as enthusiasts, advocates and technical knowledge.
There are a number of BIG Data and Analytics presentations at the UKOUG Conference in Birmingham (4th Dec – 7th Dec).
I’ve worked my way through the agenda grids for each day of the conference and I’ve come up with the following list. If you are interested in BIG Data and Analytics these presentations are a must see
| Monday | 12:15-13:15 | Exadata Live – Graham Wood – Hall 7A |
| 5th Dec | ||
| Tuesday | 9:00-10:00 | Big Data-Are you ready – Mark Townsend – Hall 1 |
| 6th Dec | 10:10-10:55 | Who’s afraid of Analytic Functions – Alex Nuijten – Hall 5 |
| 11:15-12:15 | Analysing Your Data with Analytic Functions – Carl Dudley – Hall 9 | |
| 16:40-17:40 | Mobile Analytics using OBIEE 11g – Jon Mead – Exec Room 1 | |
| Wednesday | 9:00-10:00 | Oracle 11g Database Automatic Parallelism – Joel Goodman – Hall 9 |
| 7th Dec | 15:20-16:05 | How to Deploy your Oracle Data Miner in a Live Environment - me |
The BIWA SIG is hosting a techcast called “Using Oracle R Enterprise” on Wednesday 30th November, 2011 at noon EST (approx 6pm GMT).
The TechCast is being presented by Mark Hornick, Senior Manager, Oracle Advanced Analytics Development
URL for TechCast: https://stbeehive.oracle.com/bconf/confDetails?confID=334B:3BF0:owch:38893C00F42F38A1E0404498C8A6612B0004075AECF7&guest=true&confKey=608880
-- Web Conference ID: 303397
-- Web Conference Key: 608880
-- Dialup: 1-866-682-4770, ID 5548204, passcode 1234
Several analytic tool vendors have added R-integration to their software. However, Oracle is the largest company to throw their weight behind R. On October 3, Oracle unveiled their integration of R: Oracle R Enterprise (http://www.oracle.com/us/corporate/features/features-oracle-r-enterprise-498732.html) as part of their Oracle Big Data Appliance announcement (http://www.oracle.com/us/corporate/press/512001).
Oracle R Enterprise allows users to perform statistical analysis with advanced visualization on data stored in Oracle Database. Oracle R Enterprise enables scalable R solutions, while facilitating production deployment of R scripts and Hadoop based solutions, as well as integration of R results with Oracle BI Publisher and OBIEE dashboards.
Check out the Oracle YouTube video (5min), that demos how an Exalytics application that can analyse almost a billion records instantly.
If you are attending the UKOUG Conference in Birmingham, Jon Mead (RittmanMead) is giving a presentation called “What can Exalytics do for me?” and is on Tuesday 5th December @15:35, in the area above the box office.
This is the second of a two part blog posting on using an Oracle Data Mining model to apply it to or score new data. The first part looked at how you can score data the DBMS_DATA_MINING.APPLY procedure for scoring data batch type process.
This second part looks at how you can apply or score the new data, using our ODM model, in a real-time mode, scoring a single record at a time.
PREDICTION Function
The PREDICTION SQL function can be used in many different ways. The following examples illustrate the main ways of using it. Again we will be using the same data set with data in our (NEW_DATA_TO_SCORE) table.
The syntax of the function is
PREDICTION ( model_name, USING attribute_list);
Example 1 – Real-time Prediction Calculation
In this example we will select a record and calculate its predicted value. The function will return the predicted value with the highest probability
SELECT cust_id, prediction(clas_decision_tree using *)
FROM NEW_DATA_TO_SCORE
WHERE cust_id = 103001;
CUST_ID PREDICTION(CLAS_DECISION_TREEUSING*)
---------- ------------------------------------
103001 0
So a predicted class value is 0 (zero) and this has a higher probability than a class value of 1.
We can compare and check this results with the result that was produced using the DBMS_DATA_MINING.APPLY function (see previous blog post).
SQL> select * from new_data_scored
2 where cust_id = 103001;
CUST_ID PREDICTION PROBABILITY
---------- ---------- -----------
103001 0 1
103001 1 0
Here we can see that the class value of 0 has a probability of 1 (100%) and the class value of 1 has a probability of 0 (0%).
Example 2 – Selecting top 10 Customers with Class value of 1
For this we are selecting from our NEW_DATA_TO_SCORE table. We want to find the records that have a class value of 1 and has the highest probability. We only want to return the first 10 of these
SELECT cust_id
FROM NEW_DATA_TO_SCORE
WHERE PREDICTION(clas_decision_tree using *) = 1
AND rownum <=10;
CUST_ID
----------
103005
103007
103010
103014
103016
103018
103020
103029
103031
103036
Example 3 – Selecting records based on Prediction value and Probability
For this example we want to find our from what Countries do the customer come from where the Prediction is 0 (wont take up offer) and the Probability of this occurring being 1 (100%). This example introduces the PREDICTION_PROBABILITY function. This function allows use to use the probability strength of the prediction.
select country_name, count(*)
from new_data_to_score
where prediction(clas_decision_tree using *) = 0
and prediction_probability (clas_decision_tree using *) = 1
group by country_name
order by count(*) asc;
COUNTRY_NAME COUNT(*)
---------------------------------------- ----------
Brazil 1
China 1
Saudi Arabia 1
Australia 1
Turkey 1
New Zealand 1
Italy 5
Argentina 12
United States of America 293
The examples that I have give above are only the basic examples of using the PREDICTION function. There are a number of other uses that include using the PREDICTION_COST, PREDICTION_SET, PREDICTION_DETAILS. Examples of these will be covered in a later blog post
Oracle in Ireland is hosting a session called Data Centre Transformation on 7th December (9:30-13:00), in the Guinness Storehouse, St James Gate, Dublin 8.
The agenda for this session is
| 9:00 | Registration & Coffee |
| 10:00 | The 21st Century Data Centre, Delivered by Oracle Solaris – Mike Ramchand |
| 10:30 | Oracle Enterprise Manager 12c – John Caulfield, Solutions Director |
| 11:00 | Oracle Virtualised Systems (VM 3.0) – Dave Patterson, Oracle Hardware |
| 11:30 | Coffee Break |
| 12:00 | Transformative Oracle Storage Solutions – Neil Caughey, Oracle Storage Business Unit |
| 12:30 | Extreme Performance with Oracle Exadata and Exalogic – Brian Grant, Oracle Exalogic Business Development Manager |
To book your place on this event email oracle.events@ketchumpleon.com
Or register by following this web link.
I wont be at this event as I’ll be presenting in the afternoon at the UKOUG conference in Birmingham.
This is the first of a two part blog posting on using an Oracle Data Mining model to apply it to or score new data. This first part looks at the how you can score data using the DBMS_DATA_MINING.APPLY procedure in a batch type process.
The second part will be posted in a couple of days and will look how you can apply or score the new data, using our ODM model, in a real-time mode, scoring a single record at a time.
DBMS_DATA_MINING.APPLY
Instead of applying the model to data as it is captured, you may need to apply a model to a large number of records at the same time. To perform this bulk processing we can use the APPLY procedure that is part of the DBMS_DATA_MINING package. The format of the procedure is
DBMS_DATA_MINING.APPLY (
model_name IN VARCHAR2,
data_table_name IN VARCHAR2,
case_id_column_name IN VARCHAR2,
result_table_name IN VARCHAR2,
data_schema_name IN VARCHAR2 DEFAULT NULL);
| Parameter Name | Description |
| Model_Name | The name of your data mining model |
| Data_Table_Name | The source data for the model. This can be a tree or view. |
| Case_Id_Column_Name | The attribute that give uniqueness for each record. This could be the Primary Key or if the PK contains more than one column then a new attribute is needed |
| Result_Table_Name | The name of the table where the results will be stored |
| Data_Schema_Name | The schema name for the source data |
The main condition for applying the model is that the source table (DATA_TABLE_NAME) needs to have the same structure as the table that was used when creating the model.
Also the data needs to be prepossessed in the same way as the training data to ensure that the data in each attribute/feature has the same formatting.
When you use the APPLY procedure it does not update the original data/table, but creates a new table (RESULT_TABLE_NAME) with a structure that is dependent on what the underlying DM algorithm is. The following gives the Result Table description for the main DM algorithms:
For a Classification algorithms
case_id VARCHAR2/NUMBER
prediction NUMBER / VARCHAR2 -- depending a target data type
probability NUMBER
For Regression
case_id VARCHAR2/NUMBER
prediction NUMBER
For Clustering
case_id VARCHAR2/NUMBER
cluster_id NUMBER
probability NUMBER
Example / Case Study
My last few blog posts on ODM have covered most of the APIs for building and transferring models. We will be using the same data set in these posts. The following code uses the same data and models to illustrate how we can use the DBMS_DATA_MINING.APPLY procedure to perform a bulk scoring of data.
In my previous post we used the EXPORT and IMPORT procedures to move a model from one database (Test) to another database (Production). The following examples uses the model in Production to score new data. I have setup a sample of data (NEW_DATA_TO_SCORE) from the SH schema using the same set of attributes as was used to create the model (MINING_DATA_BUILD_V). This data set contains 1500 records.
SQL> desc NEW_DATA_TO_SCORE
Name Null? Type
------------------------------------ -------- ------------
CUST_ID NOT NULL NUMBER
CUST_GENDER NOT NULL CHAR(1)
AGE NUMBER
CUST_MARITAL_STATUS VARCHAR2(20)
COUNTRY_NAME NOT NULL VARCHAR2(40)
CUST_INCOME_LEVEL VARCHAR2(30)
EDUCATION VARCHAR2(21)
OCCUPATION VARCHAR2(21)
HOUSEHOLD_SIZE VARCHAR2(21)
YRS_RESIDENCE NUMBER
AFFINITY_CARD NUMBER(10)
BULK_PACK_DISKETTES NUMBER(10)
FLAT_PANEL_MONITOR NUMBER(10)
HOME_THEATER_PACKAGE NUMBER(10)
BOOKKEEPING_APPLICATION NUMBER(10)
PRINTER_SUPPLIES NUMBER(10)
Y_BOX_GAMES NUMBER(10)
OS_DOC_SET_KANJI NUMBER(10)
SQL> select count(*) from new_data_to_score;
COUNT(*)
----------
1500
The next step is to run the the DBMS_DATA_MINING.APPLY procedure. The parameters that we need to feed into this procedure are
| Parameter Name | Description |
| Model_Name | CLAS_DECISION_TREE -- we imported this model from our test database |
| Data_Table_Name | NEW_DATA_TO_SCORE |
| Case_Id_Column_Name | CUST_ID -- this is the PK |
| Result_Table_Name | NEW_DATA_SCORED -- new table that will be created that contains the Prediction and Probability. |
The NEW_DATA_SCORED table will contain 2 records for each record in the source data (NEW_DATA_TO_SCORE). For each record in NEW_DATA_TO_SCORE we will have one record for the each of the Target Values (O or 1) and the probability for each target value. So for our NEW_DATA_TO_SCORE, which contains 1,500 records, we will get 3,000 records in the NEW_DATA_SCORED table.
To apply the model to the new data we run:
BEGIN
dbms_data_mining.apply(
model_name => 'CLAS_DECISION_TREE',
data_table_name => 'NEW_DATA_TO_SCORE',
case_id_column_name => 'CUST_ID',
result_table_name => 'NEW_DATA_SCORED');
END;
/
This takes 1 second to run on my laptop, so this apply/scoring of new data is really quick.
The new table NEW_DATA_SCORED has the following description
SQL> desc NEW_DATA_SCORED
Name Null? Type
------------------------------- -------- -------
CUST_ID NOT NULL NUMBER
PREDICTION NUMBER
PROBABILITY NUMBER
SQL> select count(*) from NEW_DATA_SCORED;
COUNT(*)
----------
3000
We can now look at the prediction and the probabilities
SQL> select * from NEW_DATA_SCORED where rownum <=12;
CUST_ID PREDICTION PROBABILITY
---------- ---------- -----------
103001 0 1
103001 1 0
103002 0 .956521739
103002 1 .043478261
103003 0 .673387097
103003 1 .326612903
103004 0 .673387097
103004 1 .326612903
103005 1 .767241379
103005 0 .232758621
103006 0 1
103006 1 0
12 rows selected.
The UKOUG conference will be in a couple of weeks. I have my flights and hotel booked, and I’ve just finished selecting my agenda of presentations. I really enjoy this conference as it serves many purposes including, finding new directions Oracle is taking, new product features, some upskilling/training, confirming that the approaches that I have been using on projects are valid, getting lots of hints and tips, etc.
One thing that I always try to do and I strongly everyone (in particular first timers) to do is to go to 1 session everyday that is on a topic or product that you know (nearly) nothing about. You might discover that you know more than you think or you may learn something new that can be feed into some project on your return or over the next 12 months.
My agenda for the conference currently looks Very busy and in between these session, there is the exhibition hall, meetings with old and new friends, meetings with product/business unit managers, asking people to write articles for Oracle Scene, checking out possible presenters to come to Ireland for our conference in March 2012, etc. Then there is my presentation on the Wednesday afternoon.
Sunday
I’ll miss most of the Oak Table event on the Sunday but I hope to make it in time for
16:40-17:30 : Performance & High Availability Panel Session
Monday
9:20-9:50 : Keynote by Mark Sunday, Oracle (H1)
10:00-10:45 : The Future of BI & Oracle roadmap, Mike Durran, Oracle (H5)
11:05-12:05 : Implementing Interactive Maps with OBIEE 11g, Antony Heljula, Peak Indicators (H10A)
12:15-13:15 : OBI 11g Analysis & Reporting New Features, Mark Rittman (8A)
14:30-15:15 : Master Data Management – What is it & how to make it work – Robert Barnett, Hub Solutions Designs (H10A)
16:20-17:35 : Dummies Guide to Oracle ADF, Grant Ronald, Oracle, (Media Suite)
16:35-18:30 : The DB Time Performance Method, Graham Wood, Oracle (H8A)
17:45-18:30 : Performance & Stability with Oracle 11g SQL Plan Management, Doug Burns (H1)
17:45-18:30 : Experiences in Virtualization, Michael Doherty (H10A)
19:45-20:45 : Exhibition Welcome Drinks
20:45-Late : Focus Pubs
Tuesday
9:00-11:00 : Next Generation BI Architectures Masterclass, Andrew Bond, Oracle (H10B)
10:10-10:55 : Who’s afraid of Analytic Functions, Alex Nuijten, Maxima (H5)
11:15-12:15 : Analysing Your Data with Analytic Functions, Carl Dudley, (H9)
11:25-13:25 : Using a Physical Standby to Minimize Downtime for DB Release or Server Change, Michael Abbey, Pythian (Media Suite)
14:40-15:25 : How note to make the headlines, Mark Clewett, Hitachi (H10A)
14:40-15:25 : APEX Back to Basics, Paul Broughton, APEX Evangelists (H9)
15:35-16:20 : Can People be identified in the database, Pete Finnigan (H1)
16:40-18:35 : OTN Hands-on Workshop, Todd Trichler, Oracle (H8A)
17:50-18:35 : SQL Developer Data Modeler as a replacement for Oracle Designer, Paul Bainbridge, Fujitsu, (H8B)
18:45-19:45 : Keynote : Future of Enterprise Software and Oracle, Ray Wang, Constellation Research (H1)
20:00-Late : Evening Social & Networking
Wednesday
9:00-10:00 : Oracle 11g Database: Automatic Parallelism, Joel Goodman, Oracle (H9)
9:00-10:00 : Big Data: Learn how to predict the future, Keith Laker, Oracle (H8B)
10:10-10:55 : All about indexes – What to index, when and how, Mark Bobak, ProQuest (H5)
11:20-12:30 : Using Application Express to Build Highly Accessible Products, Anthony Rayner, Oracle (H8A)
12:30-13:30 : Practical uses for APEX Dictionary, John Scott, APEX Evangelists (H8A)
15:20-16:05 : How to deploy you Oracle Data Miner 11g R2 Workflows in a Live Environment – Me (H7B)
16:15-17:00 : Next Generation Data Warehousing, Kulvinder Hari, Oracle (H8A)
16:15-17:00 : Beyond RTFM and WTF Message Moments. Introducing a new standard: Oracle Fusion Applications User Assistance, Ultan O’Broin (Executive Room 7)
I know I have some overlapping sessions, but I will decide on the date which of these I will attend.
As you an see I will be following the BI stream mainly, with a few sessions on the Database and Development streams too.
This year there is a smart phone app help us organise our agenda, meetings, etc, The only downside is that the app does not import the agenda that I created on the website. So I have to do it again. Maybe for next year they will have an import agenda feature.
