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Improve this questionhttp://sql.wikis.com/wc.dll?SQL~datawarehouse tells:
- "Sid Adelman of Sid Adelman & Associates in a recent presentation observed that the Meta group estimates the cost of a single data warehouse implementation project runs around $3 million, and that is for a single, initial implementation, nowhere near the scope of providing integrated views for an entire Enterprise"
I am afraid $3 million does not tell anything to majority of ppl.
How does it relate to the cost of corresponding (by size and level of data processing of) OLTP database implementation?
Is it higher/lower? how many times?Note that OLAP solutions are usually being implemented after the costs of DBMS were already made for OLTP solutions...
Why are the costs so elevated?
Update:
Let me reformulate the question: Why are the OLAP solutions rather very rare in comparison with OLTP ones?Does the laboriousness and costs of OLAP seem too prohibitive?
Nobody seems to doubt in the need and necessity to spend money on OLTP.
Though, from the logical point of view, it is not clear to me why it is not vice versa? There are a lot of legacy data sources already accumulated even outside of DBMS...Update2:
Reformulating the question again... One can judge about professional and business activity in certain areas by activity (number and frequency) of forum posts questions, vacancies, etc. OLTP related questions has 2 orders more frequency(number) of ques开发者_开发百科tions compared to OLAP ones in this SO site. Why is it?How does it relate to the cost of corresponding (by size and level of of data of) OLTP database implementation?
The question makes no sense. You might as well ask how OLAP implementations compare with buying a new Bentley Continental Automobile. Or ask how OLAP implementations compare with an SAP ERP implementation. Or ask how OLAP implementations compare with a vacation in the South of France.
There's nothing comparable between OLAP and OLTP except that they both use a database.
Is it higher/lower? how many times?
Yes. It can be higher, lower or the same. It depends on the scope of work, not the database architecture.
Why are the OLAP solutions rather very rare in comparison with OLTP ones?
According to whom? Everyone who implements a "reporting" system that is attached to their transactional system is doing OLAP. Many, many applications are in two parts: the core transactional part and some reporting add-ons.
I wouldn't call using Business Objects or Cognos "very rare".
Does the laboriousness and costs of OLAP seem too prohibitive?
OLAP costs depend on the scope of work. There's nothing inherently prohibitive. If you install BO to do some reporting, the cost is very small. If you create a large enterprise-wide warehouse, the cost is large.
Why are the costs so elevated?
Compared with what? Companies can spend $80M US implementing SAP. That's higher. But not comparable. Companies can spend nearly $0 (under $100K) implementing a free open-source component. That's lower. But not comparable.
Why is it? OLTP related questions has 2 orders more frequency(number) of questions compared to OLAP ones in this SO site.
That's obvious. OLAP is easy. OLTP is difficult.
Also C# is the most difficult programming language. Equally obvious.
Why is it? OLTP related questions has 2 orders more frequency(number) of questions compared to OLAP ones in this SO site.
Could it be that generally experienced database developers do OLAP while OLTP is often done by application programmers with little or no database knowledge? So there is less need to ask questions and the questions they have tend to be too complex for a forum.
Could there be fewer OLAP databases because they generally need one or more OLTP databases to pull data from and that OLAP implementations often consolidate data from many OLTP databases? Could it also be that small databases and databases on some subjects don't generally need data warehousing solutions at all? Generally there is no need to develop a data warehouse if the reporting needs perform adequately aginst the OLTP database, so it is generally only as the amount of data gets very large and the reporting gets very complex that these types of projects are initiated.
I can also assure you that our Enterprise OLTP databases cost considerably more than 3 million to develop. By comparison our OLAP databases were much cheaper. We have spent less that 5% of the development time on OLAP than on OLTP. Maybe even less than 1%.
There's very little point in comparing the costs of two vastly different sets of requirements. Anyway, there is no such thing as an "average" project. OLTP refers to one type of database workload whereas OLAP refers to a set of technologies used for decision support applications. They are literally incomparable. Nor do I understand on what you are basing your idea that OLAP is "rare". OLAP is only one type of solution, inevitably the universe of all other database solutions is much bigger than just OLAP.
EDIT: Maybe you might rephrase the question this way: "Why is there less money spent on decision support database applications than there is on other types of database applications?". It depends how you define "decision support" of course. However, if you look at the proportion of most organisations' resources dedicated to "decision support" versus the resources used on doing other stuff then I think you will see the reason.
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