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Ask the Experts Archive
ARCHIVE OF QUESTIONS & ANSWERS FOR DW BASICS
I would like to know which certification for data warehousing is most widely accepted and how to go about it. Is certification worth the time, effort and expense?
I've heard some discussion about capitalizing our data warehouse rather than expensing it. This means the data warehouse would appear on our company's books as an asset and we would amortize it. Is this legitimate? Do you have any recommendations on how we should go about it?
What is real-time data warehousing? How do we recover the session when it breaks in middle of running a performance recovery of the session?
Please define data reconciliation and database reconciliation. I also need a definition of data synchronization.
What do you think is the optimal organization
structure for business intelligence and data warehousing for an organization?
Would you interview top executives (CEO, COO, CFO), vice presidents and directors of functional areas separately or as a group for the collection of business requirements via interviews?
When planning for an enterprise data warehouse, what types of investment should be planned for in the way of technology infrastructure - mainly computer hardware and software platforms (servers, databases, storage, OS, etc.)? Let?s say this is a 1 terabyte EDW to start, please estimate requirements and rough costs.
I am looking for information on evaluating the success or failure of a data warehouse after implementation from a business point of view. I am looking for a methodology and tools for doing
this if one is available.
We are currently evaluating several BI solution options and realized that there are solutions that manage by data kept in data warehouses and those that manage by data kept in analysis cubes.
Could you advise which is a better approach of managing data?
The new trend has been demanding real-time data
from the data warehouse: 1) to generate operational report at high
frequency 2) to provide a golden source (real-time reference data) for
multiple OLTP Applications. Which is the right ETL tool to extract data
from multiple OLTP sources with no latency and importantly no performance
impact on OLTP. RDBMSs are Informix, Oracle and DB2 UDB?
Is there a report that itemizes the costs of reporting solutions for each vendor? How do the vendors arrive at their
cost per implementation? We are considering several options and need as
much information as possible. This is a solution that requires both ad hoc
and static reporting for a large company. We initially want to generate 60
reports and have ad hoc capabilities.
Do you have a standard template for gathering business requirements for enterprise data requirements project?
It has been suggested that we can skip user acceptance testing of the Dimension tables in order to speed up implementation. This is regardless of whether the tables are new or
existing. I am adamantly opposed to the idea. I would appreciate your
thoughts on the subject.
I am working on structuring a data system for a German bank that needs a
data warehouse that will allow access by different departments in the
bank. The architecture needs to support the potential for a merger or
acquisition. I'm looking for information about the capability and
efficiency of a data warehouse that will support the integration of data
requirements from multiple departments and from more than one
organization. Are there any resources that address this topic?
I?m trying to find out how a data warehouses architecture i.e., central data warehouse with distributed OLTP, affects the type of methodology used to create the data warehouse e.g., top-down, bottom-up, hybrid.
It's always scary to trot out one's core beliefs in front of the pros, but
I need to hear your constructive criticism. The following are my views,
and then a response from a colleague who believes in a very different
approach. Who is right?
What is the difference between federated data warehousing and distributed data warehousing?
Where can I find a case study on the data
warehousing life cycle? I?ll be building a cube in a star schema
within the pharmaceuticals industry domain.
I am preparing a document for effort estimation
for data warehousing projects. Currently we are using WBS (work breakdown
structure) for effort estimation. I want to have some ideas about how
others are doing the estimation.
I am looking for definitions of business and
executive sponsors as this function pertains to an information
We do not have any sponsors. We have an existing IW. We will be
implementing an ETL tool to replace programs and move the IW from Oracle on UNIX to DB2 on the
We can have a staging area between extract and
transform or we can have staging area between transform and
load. I would
like to know three to four advantages and disadvantages of each.
I am a DBA, new to data warehouse concepts and would appreciate
if you could reply to my questions concerning issues of
architecture as I prepare to implement a one terabyte warehouse.
I am working with a client that is currently enforcing a
standard that does not allow direct query access to data mart
dimensions and fact tables. They have created database views for
this purpose. I would like to know if this is standard practice
within other organizations. I would like to get other opinions
and experiences on the matter because this is the first time I
have seen such a standard.
What are the major risk factors in a data warehouse
project implementation? Do you have any case studies for these
Should I use a work breakdown structure in a data
Can a single data staging area serve two masters, operational
(ODS) and analytic (data warehouse)? Is a single data staging
area serving both requirements (operational and analytic) common
data warehouse industry?
I am a Ph.D student in engineering management at
the George Washington University. My dissertation topic is
adapting a method for estimating development costs of data
short-term goal is to collect data on completed data warehouse
need help on finding completed data warehouse projects. Can you
Is a data mart defined by its size or is it defined by the
specific business process it supports?
What is the difference between the terms "business
intelligence" and "data warehousing?" People seem to be using
these terms on an interchangeable basis.
Are there any articles, books, or papers on maintenance issues for data warehousing systems? I?m looking for the following:
Read It! (Posted June 4, 2003)
What is a distributed data warehouse?
How effective is data warehousing for the manufacturing industry?
I have trouble selling the data warehouse to management. They
that the minimal reporting capabilities they have today
constitutes a data
warehouse. How can I sell the concept and the benefits of a true
warehouse (whatever that is)?
I am currently involved with a start-up for-profit graduate and
undergraduate educational project but I want part of the
advanced database course to include data warehousing ("Now kids,
forget everything youlearned about OLTP databases...") and my
questions are: 1) Anyone have textbooks to recommend? In fact,
are there any textbooks? 2) What topics should be part of a
curriculum? 3) Do non-vendor specific teaching materials exist?
I am new to data warehousing. I am working on a DW
project. The role of my team is to do system testing for the
would like to know how can we estimate the system testing effort
project. Is there any standard method for estimating the effort
for system testing?
We are involved with a DW strategy and planning a CRM
strategy. The company needs information now, and we can't wait
for the CRM
implementation. What can we do to integrate the two strategies?
we have to consider the actual information requirements that we
satisfy with the actual operational systems and the CRM strategy
implemented in 2004.
My customer information is spread over multiple systems on
different platforms (Windows, UNIX, mainframe). The requirement
is to create a customer data warehouse for dimensional analysis.
What type of architecture should one follow? What tools are
available? What is the possibility of using a tool like MQ
We are trying to create a policy on information
reporting that would identify the types of reports that should
our DW vs. those that should come from our operational systems.
provide some guidance on how we could create such a policy?
I am currently a student at college. We have an
assignment to do on CRM. We have to develop a CRM and convince
of directors not to outsource our department (which is the
department). Where could I find information on why we should not
I want to know how to estimate the total project cost to
implement a data warehouse. Are there any tools available to
estimate the project cost, specifically for data warehouses or
for related projects?
What is the industry standard benchmark for data warehouse
customer usage? I am particularly interested in comparing the
number of active user accounts versus the total of registered
accounts. What would that suggest is a reasonable level of
percentage usage over the long run?
Should a data warehouse be used to produce management
reports in specific subject areas that will be sent to the
week or month? Our managers think that the data warehouse should
produce those reports. Where can I find documentation on how the
warehouse should be used?
The ROI for data warehousing is an interesting approach. Anyway
only focusing on monetary aspects. Do you know about methods
profitability analysis (including all the benefits and costs) in
What are some of the companies with the biggest data
Before I begin, I must stress that I am an absolute beginner to
data warehousing. I am trying to find good references to how
data warehousing might increase the efficiency of the
organization and how such a capability might be implemented.
Some starting hints or good book references would be a quantum
leap over my existing knowledge.
Can you provide me with the top data warehouse solution providers?
I've just finished my MBA (systems) and I am looking forward to a career in data warehousing. Kindly advise me on the specific skill sets I need to develop to make it big in the field of data warehousing.