Well, anyone can pick up the definition of relational model by Googling and reading the Wikipedia page on this. What I want to point out, based on my experience, is that relational model is a clean way to sort out concepts around data in an enterprise situation. There have been other types of models in the database theory, such as hierarchy and network models. Relational models fit the need of OLTP system design quite perfectly and have been the dominant modelling method for more than 40 years. Right now, there are object oriented models, and other variations of relational models exist in the industry.
One of the key challenges to the relational modelling, is that the management of history inside a model. In the relational theory, the 1NF (Normal Form), 2NF, to BCNF,4NF, and 5NF are even not enough to keep historical data in a clean way. People have introduced 6NF to manage history data in relational theory.
The key concepts in relational modelling are, for example, entity, entityset, relationship, relationshipset, one-to-many, many-to-many, one-to-one relationships, etc. So, how does people in the enterprise world understand a data model? Diagrams, yes, the diagrams. Most people could not understand the modelling tools such as IDA, RSM, WBM, until they see the diagrams shown in the tool. Diagrams are the key output in a modelling session.
So, improve your "diagramming" skill if you plan to be a modeller :)
Friday, September 24, 2010
Friday, September 10, 2010
How data modelling has been in the enterprises
Well, it all depends...
For an enterprise where modelling is considered as an important step towards the maturity of IT development, process, functionality, and data modelling (and others like user experience) are an important part of developers' life.
What's interesting to see is that data modelling has not been considered as so important compared to functionality or process parts in most organizations. It is not difficult to understand this. The E-R modelling discipline has served most transnational system designs and other tricks, such as multidimensional modelling has been well used in most situations before. And I believe many S-M or close to L size organizations still have no problem of only doing some basic E/R modelling and hire good DBAs to take care of the rest for the next decades.
The difference is that some, I cannot find a better word than some, organizations do have good business in the past and have acquired different lines of business and owned different systems for many years. When they do the integration of IT solutions (they will end-up doing this most of the time), it has been extremely difficult to integrate on the process, or functionality. or any other levels. Data model is the only possible easy way to let the integration succeed. So, it is just the recent years that many large or X large organizations started to realize the importance of controlling their data, meaning the data modelling, data quality, master data, and meta-data.
Another angle is to look at the vendors of data modelling tools and data models. There have been quite a lot of data modelling tools (we mentioned this in a previous note) in the market but there are only a few leaders in the market, most of whom also provide large database engines. And vendors of data models are extremely limited to giant software vendors. So this market up-to-now has been very limited.
This phenomenon looks interesting and even funny to me. Most of people talk about information explosion in the new IT era. But it is also these people who choose not to understand their data, which is then translated to information for some purposes. :)
For an enterprise where modelling is considered as an important step towards the maturity of IT development, process, functionality, and data modelling (and others like user experience) are an important part of developers' life.
What's interesting to see is that data modelling has not been considered as so important compared to functionality or process parts in most organizations. It is not difficult to understand this. The E-R modelling discipline has served most transnational system designs and other tricks, such as multidimensional modelling has been well used in most situations before. And I believe many S-M or close to L size organizations still have no problem of only doing some basic E/R modelling and hire good DBAs to take care of the rest for the next decades.
The difference is that some, I cannot find a better word than some, organizations do have good business in the past and have acquired different lines of business and owned different systems for many years. When they do the integration of IT solutions (they will end-up doing this most of the time), it has been extremely difficult to integrate on the process, or functionality. or any other levels. Data model is the only possible easy way to let the integration succeed. So, it is just the recent years that many large or X large organizations started to realize the importance of controlling their data, meaning the data modelling, data quality, master data, and meta-data.
Another angle is to look at the vendors of data modelling tools and data models. There have been quite a lot of data modelling tools (we mentioned this in a previous note) in the market but there are only a few leaders in the market, most of whom also provide large database engines. And vendors of data models are extremely limited to giant software vendors. So this market up-to-now has been very limited.
This phenomenon looks interesting and even funny to me. Most of people talk about information explosion in the new IT era. But it is also these people who choose not to understand their data, which is then translated to information for some purposes. :)
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