New PDF release: Building a Data Warehouse: With Examples in SQL Server

By Vincent Rainardi

ISBN-10: 143020527X

ISBN-13: 9781430205272

ISBN-10: 1590599314

ISBN-13: 9781590599310

I will be able to inform - this writer has equipped genuine info warehouses. This booklet has such a lot of genuine international program options, distilled into lower than 500 pages. I.E. it's not now not a bible publication, that which places you to sleep, even though it is a smart reference e-book. it truly is Inmon and Kimball agnostic - large profit right here. whereas the DW toolkit books are nice, they're basically nice for Kimball warehouses. Being within the Inmon camp, I savour the authors' assurance of the innovations of the Operational facts shop, and Normalized facts shop. This booklet will be the 1st e-book you learn in development an information warehouse. even though the categorical sql code examples convey SQL Server code, all techniques might be utilized to Oracle, and so on. just a couple lawsuits. there's a loss of assurance for modeling localization, i.e. modeling for neighborhood language specifications of the clients. the writer also needs to point out that information Modeling instruments, comparable to ErWin, PowerDesigner (best IMO), or ER/Studio can relatively improve metadata modeling, and documentation, even if he covers metadata rather well. That apart, I nonetheless provide this booklet a five superstar ranking, in lieu of all of the idea books in the market, which lack actual global program examples.

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Additional info for Building a Data Warehouse: With Examples in SQL Server (Expert's Voice)

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Near real-time approaches can be implemented by using a mini-batch with two- to fiveminute frequency, which pulls the data from the stage area instead of using triggers. This minibatch also does the normal ETL job—transforming the data and loading it into the data warehouse dimensional database. The mini-batch can also pull the data directly from the source system, eliminating the need of modifying the source system to update the staging area. Summary This chapter introduced data warehousing. I showed many examples, with the hope that they would make the concepts easier to understand and would enrich your experience.

Master data consists of the entities that describe the business event. Master data consists of the answers of who, what, and where questions about a business transaction. In the previous example, the master data is customer, product, and brand. Here’s the second example: 1,000 bus drivers from 10 different transport companies are driving 500 buses around 50 different routes in a town. Each route is served 20 times a day, which is called a trip. The business process here is driving one trip. That is the transaction.

An example of a step is extracting particular data from a source data store or performing certain data transformations. The ETL packages in the data warehouse are managed by a control system, which is a system that manages the time each ETL package runs, governs the sequence of execution of processes within an ETL package, and provides the capability to restart the ETL packages from the point of failure. The mechanism to log the result of each step of an ETL process is called ETL audit. Examples of the results logged by ETL audits are how many records are transformed or loaded in that step, the time the step started and finished, and the step identifier so you can trace it down when debugging or for auditing purposes.

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Building a Data Warehouse: With Examples in SQL Server (Expert's Voice) by Vincent Rainardi

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