Rittman Mead Blog - Data Warehousing

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Data Warehousing

A collection of 205 posts

The One Mapping Paradigm

Here at Rittman Mead we have been working on some new methodology and design patterns for ETL. We have long realised that the bottleneck in Business Intelligence and Data Warehousing projects is ETL, so we have been prototyping new techniques to approaching this and trialling them at client's

Oracle BI Suite EE

Oracle Data Warehouse Global Leaders Webcast

I'm honored to be delivering a webcast for the Oracle Data Warehouse Global Leaders Program on Tuesday, March 22 at Noon EST. This is an elite program for key global data warehousing customers and is managed by the Oracle data warehousing product management team. It also provides a

Moving Data

I just looked at the Rittman Mead Blog archive and saw the last post that was written by me was back in August 2010! Where has the time gone? Some of the time has been spent preparing and giving conference and user group talks, (as I write this I am

Oracle BI Suite EE

Looking forward to RMOUG

I'm currently on a plane headed to Denver for the annual RMOUG Training Days conference. This is my second year speaking at RMOUG, which is the largest regional Oracle user group conference in the country (or so they tell me). RMOUG always has a strong database and DBA

Transcend Part 2: Dimensions

In the last post [https://www.rittmanmead.com/blog/2010/12/01/transcend-part-1-mappings/], I described the concept of a "Mapping" entity in Transcend as a bundling of pre- and post-mapping processes that can be executed with a single call. The "Dimension" entity is very similar. In

Transcend Part 1: Mappings

If you read the blog regularly, then you know that Rittman Mead offers a product called Transcend that is designed to interact with the Oracle Database to make some of the heavy-lifting in ETL mappings very simple. Because we recently released version 2.5 of Transcend, I thought I'

Partitioning Fact Tables, Part 1

I'm dogmatic about certain aspects of data warehousing. For instance, fact tables should be range partitioned by DATE. I tell my clients all the time: you will have a very difficult time persuading me otherwise. But they always try: they argue about all the attributes that are more

Oracle BI EE 10.1.3.4.1 – Do we need measures in a Fact Table?

I know this blog title can be classified as a deviation from my more conventional ones but i have been planning on writing this for a while now, so hopefully this should be of some interest to everyone. As we start working with BI EE more and more, we get

Realtime Data Warehouse Challenges - Part 1

In a previous part of my notes on Realtime Data Warehousing I mentioned some of the challenges of reducing latency. The piece picked up quite a few comments - to which I say thanks to all that posted responses. One of the comments from Matt Hosking mentioned some of the

Suncoast Oracle Users Group, May 27, 2010

I'm honored and excited to be speaking at the Suncoast Oracle Users Group (SOUG) [http://soug.acomp.usf.edu/] monthly meeting on May 27th, 2010, at the PricewaterhouseCoopers [http://soug.acomp.usf.edu/meetings.php] facility at 3109 W. Martin Luther King Blvd., Tampa, FL 33607. Much appreciation

Adding Default Rows with OBIEE

When looking at a typical dimensional model, there are cases when the application of one or more dimension tables may not make sense for particular fact rows. We handle these situations with special rows in the dimension table that specify this lack of relationship, sometimes known generically as "default&

Realtime BI Is Not Realtime DW

This posting is slightly edited to clarify that the majority of the post is about using transactional or transactionally structured sources for reporting. One of the points I make early on in my talk "Getting Real Data Warehouse Loading as it Happens" is that realtime business intelligence is

Wrapping up Collaborate 10

It's been a fun week in good old Las Vegas. Though in the end I broke even at the tables, I enjoyed holding a large amount of the Mandalay Bay's money for them for two or three days, just to give it all back to them

Exadata in Retail Presentation

I recently gave a presentation at the Oracle Extreme Performance Data Warehousing Seminar [http://www.oracle.com/webapps/events/EventsDetail.jsp?p_eventId=103412&src=6802174&src=6802174&Act=115] about a project we have been working on with a client. The client is in the retail

Realtime Data Warehouses

In a little over two weeks I will be giving my Real Time Data Warehousing talk at Collaborate [http://collaborate10.ioug.org/Education/BIWATrainingDays/tabid/83/Default.aspx] 10 in Las Vegas. I will cover a variety of techniques and not just change data capture. However, in my opinion, CDC

Transcend and Segment-Switching

As you read this most recent post on the capabilities of Transcend, I'd like to pose a question to you: would you consider using Transcend in your environment if it was open-sourced? Currently, we implement Transcend as part of the Rittman Mead Rapid Deployment Framework for our clients,

Configuring ODI 10.1.3.6 to use Oracle Golden Gate for Changed Data Capture

If you've an interest in Oracle data warehousing and ETL, you'll probably have noticed the recent announcements around the Oracle acquisition of Golden Gate [http://www.oracle.com/goldengate/index.html]. Golden Gate were a company that produced a cross-platform data replication and changed data capture

Thoughts on Change Data Capture

In little over a month I will be in Las Vegas speaking at Collaborate 10. There is a lot of BI / DW talks this year and for the first time with BIWA Training Days branding [http://collaborate10.ioug.org/Education/BIWATrainingDays/tabid/83/Default.aspx#view] . Rittman Mead will be

Oracle 11g Pivot

One of the things that I often come across is the "up-dateable fact", that is a fact that starts life "incomplete" and changes overtime. Examples include things such as support calls that start life as "open" then progress through "responded", "resolved&

Data Warehouse Fault Tolerance Part 3: Restoring

Hopefully you've read the introduction [https://www.rittmanmead.com/blog/2010/02/02/data-warehouse-fault-tolerance-an-introduction/], Part 1 [https://www.rittmanmead.com/blog/2010/02/08/data-warehouse-fault-tolerance-part-1-resuming/], and Part 2 [https://www.rittmanmead.com/blog/2010/02/10/data-warehouse-fault-tolerance-part-2-restarting/]. Those posts detailed methods for building fault-tolerant ETL code, with a

Data Warehouse Fault Tolerance Part 2: Restarting

In my last post [https://www.rittmanmead.com/blog/2010/02/08/data-warehouse-fault-tolerance-part-1-resuming/], I described the First "R" in data warehouse fault tolerance: Resuming. As I mentioned in the introduction [https://www.rittmanmead.com/blog/2010/02/02/data-warehouse-fault-tolerance-an-introduction/] to this series, my goal is a triage approach

Data Warehouse Fault Tolerance Part 1: Resuming

In the introduction [https://www.rittmanmead.com/blog/2010/02/02/data-warehouse-fault-tolerance-an-introduction/] to this series of posts, I spoke briefly about data warehouse fault tolerance and the unique challenges resulting from high data volumes combined the batch load window required to create them. I then defined the goal: a layered

Data Warehouse Fault Tolerance: An Introduction

With so much of the blog devoted to OBIEE, OWB and Essbase lately, I felt like it was time to do a few database-related postings. In the past, when I've posted database content to the blog, I usually gravitate toward ETL-related features: those that waffle between database administration

Capturing Change (Part 2)

In the previous [https://www.rittmanmead.com/blog/2009/12/08/capturing-change-part-1/] part I outlined the business need for writing our own CDC routines and started to outline some of the issues we would need to resolve. Here I shall outline the approach we took and describe how to go

Transcend and Constraint Maintenance

In this [https://www.rittmanmead.com/blog/2009/12/21/transcend-and-index-maintenance/] posting, I explained the Transcend product as a new offering here at Rittman Mead, and I went on to demonstrate it's use with index maintenance. Now, I'd like to demonstrate another staple of data warehouse