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Data Warehouse Listings
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Total:
105 | Displaying: 91 - 100 | Pages: << 1 2 3 4 5 6 7 8 9 10 >> |
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In order to be effective, data warehouse developers need to show tangible results quickly. At the same time, in order to build a data warehouse properly, you need a data model. And everyone knows that data models take huge amounts of time to build. How then can you say in the same breath that a data model is needed in order to build a data warehouse and that a data warehouse should be built quickly? Aren’t those two statements completely contradictory?
The answer is — not at all. Both statements are true and both statements do not contradict each other if you know what the truth is and understand the dynamics that are at work.
Updated: 05/25/2006
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In today’s business world, data warehouses are increasingly being used to help companies make strategic business decisions. To understand how a warehouse can benefit you and what is required to manage a warehouse, you must first understand how a data warehouse is constructed and established. Some of the challenges associated with implementing a data warehouse are understood by answering these questions:
+ What is the quality of data in the warehouse?
+ What are the definitions of the data elements in the warehouse?
+ How current should the warehouse data be?
+ How can you correlate warehouse data to operational data?
+ What is the physical size of a warehouse?
+ What hardware and software will be used for the warehouse?
Updated: 05/25/2006
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“There is never enough time to do something right the first time, but always enough time to do it over again.” Most readers have probably lived that cliché many times, even though they really want to do what is necessary to avoid rework. Obviously, rework involves lost productivity, and the need for rework implies that the initial results failed to meet the needs of the business or users in some fashion.
This article describes mistakes that development teams may make in an application development project during development and implementation of a logical and physical data model. I have encountered these situations many times over the last 15 years (and even made some of them myself in the earlier years). The goal of the article is to allow you to learn from other people’s experiences and increase the chances of success on the first try. My experience has been concentrated on Oracle databases, so most of the recommendations deal with techniques you can use with Oracle.
Updated: 05/25/2006
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The way of the world has been with open looped systems for almost as long as we have had computers. In an open looped system, a decision is made, is announced to the world at large, and the results take place in the market place. The results that have occurred in the market place are then measured by the open loop systems. There are many examples of open looped systems, such as
+ offering a new type of insurance policy for bicycle
riders
+ changing the price of Cherry Garcia at 31 Flavors
+ lowering interest rates for new home loans
+ restricting first class upgrades on United Airlines toemployees only, and so forth.
In an open looped system, a decision is made, and activity is undertaken, and the world reacts. The success or failure of the open looped system is measured by operational systems that record the subsequent interaction with the customer or consumer. There is no tight control of the sale or the customer as the results of the business decision are manifested in the market place. Business just happens “as usual” in an open loop system.
Closed loop systems are quite different from open loop systems. In a closed loop system, a decision is made, then the decision is disclosed to a mass of customers, typically (but not necessarily) through the Internet. In a closed loop system the organization making the decision is well aware of who the customer is and what reaction the customer has to the decision being made. There is very precise and immediate feedback from the customer to the business as a result of the closed loop.
Updated: 05/25/2006
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The Oracle database has many features that make it well suited to data warehousing, including support for very large databases, automated summary management, and an embedded multidimensional OLAP engine. Recent versions of Oracle have come with built-in extraction, transformation, and load (ETL) features, and it is possible to build an Oracle data warehouse using just these features, and SQL*Plus.
DBAs will, however, probably be aware that a number of vendors, including Oracle, offer tools and applications that are designed to assist with the design, build, and load of data warehouses — a type of application known as an ETL tool, with Oracle Oracle’s own offering being Oracle Warehouse Builder 10g. So, what does Oracle Warehouse Builder offer the Oracle DBA, and how can it help with the warehouse project lifecycle?
Updated: 05/25/2006
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Regular readers of this column will probably know that I work as a developer on the Oracle platform, putting together business intelligence and data warehousing applications using Oracle’s database and application server platforms. In the past, I’ve covered Oracle products such as Warehouse Builder and Oracle 10g. This month, during which I look forward to what Oracle has planned for the OLAP market, I’m going to broaden the remit and look at what Microsoft has in store as well. It’s an interesting story, as these two giants of the database industry have quite distinct and different views on how the OLAP industry will unfold, and each view has its own appeal.
Oracle has recently released version 10g of its database, which now comes with an embedded multidimensional OLAP server known as the OLAP Option. Microsoft, which so famously took the OLAP market by storm with Analysis Services that came bundled with SQL Server 2000, is due to release the long-awaited upgrade, originally code named “Yukon,” but now renamed SQL Server 2005. Oracle and Microsoft are, in their own ways with these new releases, looking to reshape the OLAP industry, and this will have big implications for DBAs who currently look after data warehouses running on traditional relational databases. So what have Oracle and Microsoft got in store, and what impact will this have on your future business intelligence applications?
Updated: 05/25/2006
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Consider if you will: an assortment of concepts, guidelines, and opinions gathered over 15 years’ experience in applying the craft of data modeling under a wide range of circumstances. Maybe not enough to fill a book, but enough for a bag of tricks: portable, and, hopefully, applicable to many situations.
Updated: 05/25/2006
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Live DataStage Interview Questions with answers.
Updated: 05/24/2005
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Informatica Interview Questions with Answers
Updated: 03/29/2005
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DataStage Interview Questions with Answers
Updated: 03/29/2005
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Data Warehouse Listings
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Total:
105 | Displaying: 91 - 100 | Pages: << 1 2 3 4 5 6 7 8 9 10 >> |
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