Home > Ask the Data Management Experts > DBMS and data warehousing Questions & Answers > Centralized database systems vs. data silos for master data storage
Ask The Data Management Expert: Questions & Answers
EMAIL THIS

Centralized database systems vs. data silos for master data storage

Mark Whitehorn EXPERT RESPONSE FROM: Mark Whitehorn

Pose a Question
Other Data Management Categories
Meet all Data Management Experts
Become an Expert for this site


Tips, expert advice and sample chapters
Digg This!    StumbleUpon Toolbar StumbleUpon    Bookmark with Delicious Del.icio.us    Add to Google


>
QUESTION POSED ON: 14 November 2007
We are engaged in a data integration/business process re-engineering. We have two options -- a single, centralized database storing all master data, or a series of silos (books of record), one for each functional area. Which is the better approach, given this re-engineering work is incremental and not linear (we may "fix" business areas out of order from the business process).

>
EXPERT RESPONSE
Given the complexity of even the simplest business intelligence project, I cannot, in all conscience, give you an answer telling you which to use. I'd need much more information to be that specific. But I can, hopefully, give you a flavor of the way in which I would approach the problem.

Always the most important question, and probably killer in this case is "What do the users of the system want from it?"

For example, suppose you have three functional areas -- Finance, Human Resources and Sales:

Now imagine that your users consistently want information that can only be produced using data from all three areas; then you essentially have to build a centralized data warehouse -- the question is answered. The bad news is that such systems are typically much more challenging to build. Oddly, the problem with building a centralized system hasn't so much to do with technical aspects (data volume, merging the data and so on) -- it often has more to do with human issues, such as getting the users to agree to the definition of data. This is not to imply that the technical problems are trivial, but they pale into insignificance when measured against dealing with the internal politics of a large enterprise. And definitions are often as much a matter of politics as of simple partiality.

Alternatively, imagine that you find that each set of information that the users request only requires data from within one functional area to answer. So, finance people only ask for information in the finance domain, and so on. In that case, it is very tempting to go for the silo (or books of record) approach.

However, even then, you have to be careful. Suppose that both finance and HR contain information about salaries and departments. Both can produce figures for the salary expenditure for each department. As long as this information is only used within the relevant departments then all is well. But image for a minute that the heads of both departments attend a meeting and present their figures as definitive. If we want to avoid a fist fight in the boardroom we may find that it is still essential to unify the meaning of the data across those systems. If we do that, we have done most of the work of centralizing it so that even if the information can be satisfied from silos, we may still eventually see a centralized system as the better long term solution.

To summarize: If the BI project is mainly driven by a business need to consolidate and coordinate the information that will be used by the enterprise as a whole, then centralize. If not, and you are sure there are no long term implications, then silos are fine.


Sound Off! -   Be the first to post a message to Sound Off!


Digg This!    StumbleUpon Toolbar StumbleUpon    Bookmark with Delicious Del.icio.us    Add to Google


RELATED CONTENT
DBMS and data warehousing
Data warehousing, data mining and data querying: Terms and definitions
The difference between data definition language (DDL) and data manipulation language (DML)
What is an operational data store vs. a data warehouse?
Can a dimension table be a fact table for another data mart?
Top three database management system (DBMS) trends
Can I have two data warehouses?
Database administrator job roles: Organizing the DBAs
Data modeling for data warehouse projects
Data warehouse testing
Data warehouse development: Four strategic steps

Database management systems (DBMS)
The difference between data definition language (DDL) and data manipulation language (DML)
Can a dimension table be a fact table for another data mart?
Top three database management system (DBMS) trends
DB2 looks to enterprise information management to fend off Microsoft
Database administrator job roles: Organizing the DBAs
Data migration planning: Key things to remember
Logical database design
Data migration evolves from scripts to software
The latest database management system (DBMS) trends
Gartner data warehouse DBMS Magic Quadrant 2007: New tools, old mantras

RELATED GLOSSARY TERMS
Terms from Whatis.com − the technology online dictionary
data classification  (SearchDataManagement.com)
OLAP  (SearchDataManagement.com)

RELATED RESOURCES
2020software.com, trial software downloads for accounting software, ERP software, CRM software and business software systems
Search Bitpipe.com for the latest white papers and business webcasts
Whatis.com, the online computer dictionary



Search and Browse the Expert Answer Center
Search and browse more than 25,000 question and answer pairs from more than 250 TechTarget industry experts.
Browse our Expert Advice

About Us  |  Contact Us  |  For Advertisers  |  For Business Partners  |  Site Index  |  RSS
SEARCH 
TechTarget provides enterprise IT professionals with the information they need to perform their jobs - from developing strategy, to making cost-effective IT purchase decisions and managing their organizations' IT projects - with its network of technology-specific Web sites, events and magazines.

TechTarget Corporate Web Site  |  Media Kits  |  Reprints  |  Site Map




All Rights Reserved, Copyright 2005 - 2008, TechTarget | Read our Privacy Policy
  TechTarget - The IT Media ROI Experts