Comments for Business Intelligence in the 21st Century

Comment on Segmenting on Value by bibongo

bibongo — Mon, 01 Oct 2012 09:54:07 +0000

Keith, you are absolutely spot on, thanks, but I illustrate my three points with a PPT slide and I just dont know how to add another dimension but I must figure it out. I also agree about the shaky foundations and simply dont get why these type of initiatives seem to come under the Big Data banner when in fact the social data often being used for such analysis is pretty much memory stick size.

Comment on Segmenting on Value by Keith Prince

Keith Prince — Mon, 01 Oct 2012 09:23:49 +0000

Mr Bongo, I do miss your ‘direct to the heart of the matter’ approach in my working day. I’d like to add one new avenue that is being built in the customer village to the three you have listed – selling to a customer’s friends, family and followers. The avenue is being built right now but the challenge is to make sure it leads to value for the customer and the enterprise alike. But, I’m seeing very shaky foundations being laid by too many brands that just don’t ‘get it’.

Comment on Basic Fundamentals by marcothesane

marcothesane — Wed, 21 Mar 2012 16:34:45 +0000

Some type of fourteen commandments
- very nicely put
- how about sculpting them into a marble slab?

marcothesane

Comment on Copy Management as the Answer? by marcothesane

marcothesane — Mon, 27 Feb 2012 00:03:40 +0000

I forgot to add something that’s possibly obvious, but maybe the point should be made:
From the OLTP sources to the Data Warehouse and to the dimensional models – data is not copied. It’s cast into a different shape to serve a new purpose – while the old shape is still needed.
marcothesane

Comment on Copy Management as the Answer? by marcothesane

marcothesane — Sun, 26 Feb 2012 18:59:58 +0000

The Atomic Data Warehouse (cf. Inmon) is a moderately normalised data model that should be the famous Single Point of Truth.
It is the source of queries that no-one has foreseen, of queries that bring insight for strategic decisions. It is not essential, for a strategic decision, whether such a query takes a minute or 12 hours.
It usually also takes a day or two to formulate such a query in the first place.
Performance becomes important when we have many queries whose nature is known in advance. For these queries/reports, we optimise the underlying physical data model – and keep it up to date if requirements change. This physical data model can be a Kimball-ian Data Warehouse with Conformed Dimensions (they can perform very nicely) or a set – or a plethora – of multi-dimensional data marts, built as independent star models or multi-dimensional cubes stored in a proprietary fashion.
Cheers
marcothesane

Comment on The Data Warehouse by marcothesane

marcothesane — Sun, 26 Feb 2012 18:44:26 +0000

I forgot to add:
The basic principles around a data warehouse that I feel most comfortable with are still what Inmon and Kimball wrote about it – in the first half of the nineties ….

Comment on Business Intelligence is an After Thought by marcothesane

marcothesane — Sun, 26 Feb 2012 16:35:32 +0000

Hi bibongo
If the Data Warehouse/BI program in an enterprise is not an integral part of the business, then the data warehouse built does not really deserve its name.
If you say, somewhere else, that the way that we go about data warehouses has not changed very much in the last twenty years, well, that’s true. The wheel has also always been round since the day it was initially invented, and only the marketing specialists from Ship B of the Golgafrincham Ark Fleet found it essential to know what colour the wheel should be before it could be launched as a product.
The basic principles around a data warehouse that I feel most comfortable with are still what Inmon and Kimball wrote about it.
Their initial publications built the Atomic Data Warehouse (Inmon) and the Integrated Data Warehouse with Conformed Dimensions (Kimball) from the consolidated requirements of the Business (the think-global-start-local principle once put aside for argument’s sake). Consolidating here means finding an unambiguous model that satisfies as well as any possible each and every party in the enterprise with BI needs. On one hand, this takes someone who really understands what it is that makes and keeps a given company successful (and I don’t mean at the stock exchange) – and what information requirements come out of that. On the other hand, this takes someone who can put these information requirements into a complete and unambiguous shape – by filling gaps and dealing with ambiguity, and following the design principles proven so far that best suit these requirements. While the latter is what an IT person’s most important job is all about, the former is what someone capable of analysing the company’s business should bring to the table (and the fact that someone belongs to a company’s C level is no guarantee of these capabilities….). These two types of pre-requisite capabilities very rarely exist in the same head; so there were data warehousing methodologies in the nineties that suggested that two people, each with one of the two sets of capabilities, share a keyboard and a screen in a data warehousing project group.
And, yes, that’s an expensive way of building a data warehouse. But then, to me, an “Enterprise Data Warehouse” is a pleonasm. To me, there can only be one. And building a Data Warehouse is like building a city. It takes architects and politicians; it never makes everybody completely happy; it is never finished unless it’s a ghost town; and you can’t keep building it all the time because from time to time, you have to be able to live in it. And you don’t buy a city that you want to live in, you build it.
It’s already wrong in my (never too humble …) opinion to treat IT and Business separately – to me, a good IT professional developing an application is one who performs a business job in advance before someone (usually with lesser skills) needs the job to be done for a specific business event.
For a Data Warehouse, mixing technology and business is essential, and the classical methodologies, which are still valid, have always said it’s a Business *and* IT discipline, and the BI program should not reside in the IT department.

That’s my half Swiss franc …
marcothesane

Comment on Copy Management as the Answer? by José A. Ferreira Queimada

José A. Ferreira Queimada — Sat, 11 Feb 2012 16:50:28 +0000

Sometimes the data must be migrated from one platform (hardware) to another platform (hardware), due to a better performance, high availability or scalability (processing and/or storage) of the new platform.
About your considerations on datamarts… Your approach is a bottom-down architecture (coming from a corporate/enterprise data warehouse, to a small, departamental point-of-view, datamart). There is another approach: bottom-up. From datamarts to corporate data warehouse.
Which one to use? Depends on how fast the end user wants to get results.
Another use of datamarts: as a datalab. Used on analytical development environments, based on letting “play” the end user with the data… When the user gets an stable model… then it’s applied to a data warehouse scale.
And nowadays… you have the virtualization approach: take a physical data warehouse… and slide it into several virtual datamarts.
Best regards.

Comment on Good marketing enabled by data by 6 Marketing Enabled Sites

6 Marketing Enabled Sites — Wed, 04 Jan 2012 23:51:28 +0000

[...] Good marketing enabled by data | Business Intelligence in the 21st .Good marketing enabled by data. Posted on 01/06/2011 by bibongo. Every year, or at least for the last thirty years or so, [...]

Comment on Bad things happen – bad and unnecessary by bibongo

bibongo — Fri, 10 Jun 2011 11:47:23 +0000

Hey Phil – the BI messages are all over the place – justy imagine if you were the CEO of one of the companies I’ve mentioned – what sort of BI improvements would you put in place to make sure the bad experiences I’ve been reporting on don’t happen? In the example, the car rental companiy treats me like dirt – maybe they should use BI to identify key, profitable customers and give them a better service. Maybe they make this difficult because they obviously dont have a single source of the truth in terms of customer details – it all roles into one thing – sloppy use of customer data – maybe that’s my key point