Peter Scott - Rittman Mead (Page 11)

Some days the developer in me emerges and then off I go

A couple of days ago I downloaded the new release of JDeveloper. Although I had been playing with the Early Adopter version for some while I wanted to see how the official release looked. I had already recommended it to my Java developers and wanted to make sure my opinion

Some days the developer in me emerges and then off I go

Due to a dropped internet connection this entry was duplicated to here [http://pjs-random.blogspot.com/2006/02/some-days-developer-in-me-emerges-and_09.html] So this one is edited to history, and the more recent one stands. If only because Niall added a comment on the content and Bob and I did not.

Data Warehousing

Going for OLAP

To be honest, I have never implemented a data warehouse using Oracle’s OLAP option. True, I used to dabble with Oracle Sales Analyzer and Express but that was a couple of years ago and the technology has moved on. In those days we used the ROLAP model to map

Testing times

As an organisation, my employers firmly believe in working to standards; we are ISO certified, all of the technical staff in our outsourcing group have a minimum of ITIL foundation level certification. Lots of our guys also have vendor certifications in the products they use in their day-to-day working lives

Data Warehousing

Over the past few days life has been full of little distractions.

Recently we implemented some changes on a customer’s DW to improve query performance. As usual, all changes were fully tested before implementation on the production system, but because of the nature of the changes and the fact that it is difficult to adequately emulate user workload we also adopted

Plans (query and work)

One of our customers has a possible problem with a data discrepancy. Two queries that should return the same results don’t. We should get copies of the queries early next week so we can tear the two apart. We need to analyse whether the results should be the same.

A view of BI (part 3)

At the end of last year I posted the [https://www.rittmanmead.com/blog/2005/12/29/a-view-of-bi-part-1/] first [https://www.rittmanmead.com/blog/2005/12/30/a-view-of-bi-part-2/] two parts of a piece on my view of BI. Spurred on by Nicholas Goodman’s post on the Pentaho [http://www.

Data Warehousing

Average for a week

In most data warehouses there is some form of aggregation going on, sometimes in the presentation of database summary tables, sometimes in the query tool. Often this aggregation is additive over time: how many times did this IP address connect to that web page in a month, what is the

A view of BI (part 2)

Ask a group of IT specialists (especially BI specialists) what is meant by Business Intelligence and you will probably get a different answer from each person. Some will take a very narrow view and focus on, perhaps, the backend database technology, a single reporting application, or even a specific way

A view of BI (part 1)

Investment in Business Intelligence, as for all other IT endeavours, is driven by one of three factors: “Does knowing this information (at the right time) allow me to sell more?” “Does knowing this information allow me to reduce my business costs (e.g. buy cheaper, reduce headcount)?” and “Do I

Data Warehousing

Accidents waiting to happen

A while back I blogged [https://www.rittmanmead.com/blog/2005/11/07/design-matters/] about a data warehouse review we are doing for a customer. At the time I was less than impressed by the consistency of the approach to DW design and the lack of knowledge of how Oracle

Data Warehousing

Customers do odd things

You may have read in a previous Blog that I am a great believer in the use of constraints (not null, primary key and, of course, foreign key) in a data warehouse. In an Oracle data warehouse these constraints inform the query optimiser about relationships between dimension and fact data.

Data Warehousing

Pre-built materialized views

In a recent Oraclesponge posting [http://oraclesponge.blogspot.com/2005/12/ora-12034-materialized-view-log.html] David Aldridge writes about a way to get around the “ORA-12034: materialized view log younger than last refresh” error. Of course his method relies on you knowing what it is about the MV that needs to be

JDeveloper modeling (2)

Last week I posted on a JDeveloper extension for DW [https://www.rittmanmead.com/blog/2005/11/21/modelling-from-jdeveloper/] modelling tool and promised an update when I managed to get it to work. Well the guys at the IKAN have been very helpful and let me download the documentation for

Data Warehousing

Modelling from JDeveloper

In a few idle moments I downloaded the CWD4ALL [http://www.cwd4all.com/cwd4all4jdeveloper.cfm] extension to JDeveloper – I guess it is the developer in me that wants to give modelling tools a trial and as the vendor web page mentioned words and phrases such as OLAP, multi-dimensional modelling and

More design

The other day I had a rant [https://www.rittmanmead.com/blog/2005/11/07/design-matters/] about poor (in my opinion) DW design, and in particular not using the database features to the best advantage (or at all). Sometimes, though, people use the wrong features. Database links can be a

Data Warehousing

Design matters

One of our customers has asked us to review the performance of one of their legacy data warehouses. The daily data load takes far too long. There seems to be a lot we can suggest here to improve things - for a start, we need move to an incremental load

Time votes

Yesterday my thoughts returned to the topic of time, not in the Stephen Hawkin sense but the more prosaic "Data Warehouse" sense. Three questions popped up, and although I hold firm views about the answers I think there are others out there with the opposite view and indeed

Token databases

Mark Rittman [http://www.rittman.net/archives/001368.html] recently posted on the subject of column orientated databases such Sybase IQ and various SAND Technology Inc products. One aspect Mark mentioned was the use of tokens to store attribute data. In a previous role (before moving back into the mainstream

Partitioning revisited

In a previous post I asserted that range partitioning on date was commonly used in data warehouses. Date partitioning can simplify the 'retiring' of old data, make the fact load more efficient and improve the performance of user queries (after all, most users will include some form of

Data Warehousing

We know where you live

No, not a threat from a bunch of gangsters, but a reminder about a, perhaps, under used Oracle feature in data warehousing A little while back Mark Rittman reminded me of a piece he wrote on GIS enabling a data warehouse. [http://www.dbazine.com/datawarehouse/dw-articles/rittman6] People may

Data Warehousing

Materialized view usage

For one of my DW customers we adopted a materialized view-based aggregation strategy. Only the base level summaries are exposed to the query tool and the Oracle database uses query rewrite to select the 'best fit' aggregation. This was the customers first use of query rewrite, their previous

Meanwhile back with Tom Kyte

Eddie Awad asks: [http://tkyte.blogspot.com/2005/09/most-incredible-statement-i-heard-this.html#112810622682260699] How come no one has mentioned "testing"?! A very important part of developing an application (any application) is to test it again and again until the tests produce the desired results. Of course Eddie is right,

Data Warehousing

Warehouse design rant

An anonymous poster to Tom Kyte’s [http://tkyte.blogspot.com/2005/09/digging-stuff.html]Blog shared a tale of woe about data warehouse performance. Well, I felt for that poster – how can a developer put their hand on their heart (or wallet, if they are an external consultant) and

Data Warehousing

Know who your customers are - part 4

In follow-ups to recent [https://www.rittmanmead.com/blog/2005/08/31/know-who-your-customers-are-%e2%80%93-part-1/] posts [https://www.rittmanmead.com/blog/2005/09/05/know-who-your-customers-are-%e2%80%93-part-2/] some people raised a point about using basket analysis in “reverse” to segment customers. The legend that young men buy beer