Irish BI SIW

OUG Ireland BI & Tech SIGs June 2013

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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.

BI SIG

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Tech SIG

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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

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OUG Ireland 2013–Call for Presentations

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The call for presentations at the OUG Ireland Conference is now open. The conference will be on Tuesday 12th March in Dublin city centre.

It is hoped to have at a number of concurrent tracks covering all the main topic areas, including application development, database administration, business intelligence, applications, etc.

If you are interested in submitting a presentation then you need to fill in some of the detail at

OUG Ireland – Submit a Paper

Follow the OUG Ireland conversation on twitter using the tag  #oug_ire

call for papers

Events for Oracle Users in Ireland–Winter 2012

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Over the next couple months there are a number of events happening for Oracle Users in Ireland.

There are a number of OUG Ireland SIG meetings happening. These are:

11th September : Joint SIG meeting of the BI & EPM SIG and the first Tech SIG meeting

12th September : HCM SIG meeting

20th November : BI & EPM SIG.  This will be a full day SIG event.

3rd-5th December : The annual UKOUG Conference in Birmingham. There is usually a good attendance from Ireland at this conference. On the Monday night there will be the focus pubs. Join me at the Ireland table.

Oracle and the Oracle User Group have arrange to have Tom Kyte come to Dublin on 19th September, to give a number of presentations. Check out this link for more details and how to register.

Oracle will be having an Oracle Technology Day in Dublin on 15th November 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. You will need to register for this event.

Summary of Dates & Events to add to your diary.

11th September : OUG Ireland BI & EPM and Tech SIG meeting

12th September : OUG Ireland HCM SIG meeting

19th September : Tom Kyte in Dublin

15th November : Oracle Technology Day

3rd- 5th December : UKOUG Conference in Birmingham.

My OUG Ireland Conference Presentations

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Wednesday 21st March an important for the OUG Ireland as it is the annual conference. This year we are in a new venue, the Dublin Convention Centre, on the river Liffey.

After many, many years of being an attendee of my local conference, this year I will be presenting 2 presentations. Actually, I’ll be presenting one and co-presenting another.

My first presentation, will be an introduction to Oracle Data Miner, which is now part of SQL Developer. I will be talking about the new features and some features that be part of a future presentation. Most of the presentation time will be taken up with a Demonstration of using Oracle Data Miner (ODMr). I will step through a the main steps of data mining using the ODMr tool. The data set that I will be using is based on a University in the UK who wanted to look at how data mining could be used to help them manage student retention/churn.

The second presentation will be lead by Antony Heljula, of Peak Indications, with me co-presenting or butting in on some topics. This presentation will be at a much higher level. This presentation will be aimed at analysts and managers who are looking at data mining and what it can do for them.We will look at what it can be used for, who are the main people, some sample case studies/application areas, data quality issues, etc. There will be a demonstration on how you can incorporate the data mining model, developed in the first presentation, into OBIEE Dashboards. We will be using the same UK University scenario here and we will show how data mining has helped to identify specific types students that could not be identified using other means.

Check out the full conference agenda – here

There are plenty of excellent presentations, with lots of Oracle ACE’s and Oracle ACE Directors.

Some of my other activities on the day will be:

  • Talking to people about writing articles for the Oracle Scene, the user group manage. I’m the deputy editor of Oracle Scene.
  • I’m also deputy chair of the Irish BI & EPM SIG, so I’ll be trying to persuade people take part in and present at future meetings.
  • Finally and perhaps most importantly, I will be meeting other people in the Oracle world here in Ireland. Some of these people I know for 20+ years. Because of busy schedules sometimes the only time we get to catch-up is at the annual conference.

If you would like to talk to me about the topics covered in the presentations or about any of the about activities, look out for me during the day. I will be at the (free) drinks reception at the end of the day, so you can talk to me then. If that does not suit, then drop me an email and we can arrange to meet up.

ODM 11gR2–Real-time scoring of data

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In my previous posts I gave sample code of how you can use your ODM model to score new data.

Applying an ODM Model to new data in Oracle – Part 2

Applying an ODM Model to new data in Oracle – Part 1

The examples given in this previous post were based on the new data being in a table.

In some scenarios you may not have the data you want to score in table. For example you want to score data as it is being recorded and before it gets committed to the database.

The format of the command to use is

prediction(ODM_MODEL_NAME USING )

prediction_probability(ODM_Model_Name, Target Value, USING )

So we can list the model attributes we want to use instead of using the USING *  as we did in the previous blog posts

Using the same sample data that I used in my previous posts the command would be:

Select prediction(clas_decision_tree
USING
20 as age,
‘NeverM’ as cust_marital_status,
‘HS-grad’ as education,
1 as household_size,
2 as yrs_residence,
1 as y_box_games) as scored_value
from dual;

SCORED_VALUE
————
           0

Select prediction_probability(clas_decision_tree, 0
USING
20 as age,
‘NeverM’ as cust_marital_status,
‘HS-grad’ as education,
1 as household_size,
2 as yrs_residence,
1 as y_box_games) as probability_value
from dual;

PROBABILITY_VALUE
—————–
                1

So we get the same result as we got in our previous examples.

Depending of what data we have gathered we may or may not have all the values for each of the attributes used in the model. In this case we can submit a subset of the values to the function and still get a result.

Select prediction(clas_decision_tree
USING
20 as age,
‘NeverM’ as cust_marital_status,
‘HS-grad’ as education) as scored_value2
from dual;

SCORED_VALUE2
————-
            0

Select prediction_probability(clas_decision_tree, 0
USING
20 as age,
‘NeverM’ as cust_marital_status,
‘HS-grad’ as education) as probability_value2
from dual;

PROBABILITY_VALUE2
——————
                 1

Again we get the same results.

Ireland table at Focus Pub tonight

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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.

Applying an ODM Model to new data in Oracle – Part 2

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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