. Data warehousing originally grew in response to the corporate need for information--not data--and it supplies integrated, granular, and historical data to the corporation. There are many kinds of data warehouses, in large part due to evolution and different paths of software and hardware vendors. 0, defined by this author in many talks, articles, and his b-eye-network newsletter that reaches 65,000 professionals monthly, is the well-identified and defined next generation data warehouse. The book carries that theme and describes the future of data warehousing that is technologically possible now, at both an architectural level and technology level.

The perspective of the book is from the top down: looking at the overall architecture and then delving into the issues underlying the components. The benefit of this for people who are building or using a data warehouse can see what lies ahead, and can determine: what new technology to buy, how to plan extensions to the data warehouse, what can be salvaged from the current system, and how to justify the expense--at the most practical level. All of this gives the experienced data warehouse professional everything and exactly what is needed in order to implement the new generation DW 2. * First book on the new generation of data warehouse architecture, DW 2.

* Written by the "father of the data warehouse", Bill Inmon, a columnist and newsletter editor of The Bill Inmon Channel on the Business Intelligence Network. * Long overdue comprehensive coverage of the implementation of technology and tools that enable the new generation of the DW : metadata, temporal data, ETL, unstructured data, and data quality control. Чтобы оставить свою оценку и комментарий вам нужно зайти на сайт или зарегистрироваться ]]> : 0 ]]> ]]> : 0 ]]> ]]> : 0 ]]> ]]> : 0 ]]> ]]> : 0 ]]> ]]> : 0 ]]> : 0 ]]> : 0 ]]>

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    Cloud data warehouses see serious data transformation work moving to the cloud. Talend's first integration with Stitch, which it.

  • What's the difference between DDL and DML? There actually are many ways that DW 2. 0 sets the stage for a service-oriented architecture (SOA).

    The first way that SOA is accommodated is in that DW 2. 0 contains the data that SOA needs. 0 compartmentalizes data so that it is very clear as to where any given unit of data is to be found. 0 brings together many different types of data under one “roof,” there is an order to the data that service-oriented architectures require.

    0 separates data by probability of access. This means that popular, regularly accessed data is not dragged down by older, less popular data

    . This segmentation of data by probability of access enables DW 2.

    0 to provide the ultimate in performance for service-oriented architectures. Content management to power e-commerce systems takes on greater importance in personalizing customer engagement by aligning.

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  • What are primary, super, foreign and candidate keys in a DBMS? All Rights Reserved, Copyright 2005 - 2019, TechTarget These are just a few of the ways that DW 2. 0 sets the stage for service-oriented architectures.

    Stated differently, without DW 2. 0, a service-oriented architecture would have a hard time finding and processing data.

    0 is the perfect background architecture to make service-oriented architectures successful. Acing a SQL Server database audit starts with careful monitoring of how sensitive data is accessed and used so you can answer the.

  • E-commerce content management systems power personalization The second way that DW 2. 0 sets the stage for service-oriented architectures is in terms of integrating data. 0 doesn’t just contain a lot of data.

    0 mandates that data be integrated as it is brought into DW 2

    . This means that data is immediately useful.

    If data is measured in dollars, the dollar refers to the same dollar – Canadian dollars, U. Dollars or Australian dollars – not a mixture of the three.

    If data is encoded by gender, it is guaranteed that all males are “M”, not “males”, “X”, or “1. ” If data is defined as being CUSTOMER, then it is just that, not prospects or former customers. In a word, by having the data integrated into DW 2.

    0, the information is as meaningful and useful to SOA as it is easily accessible. Whether you transfer large applications, servers or databases, AWS offers a range of migration tools. Building on Part I of this series, this article will discuss how DW 2.

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    .

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    0 provides a simple technological interface. 0 requires that data be gathered together and organized by data type, when SOA needs data, it only has to deal with a single technological interface. 0, SOA would have to go into many different types of technology in order to satisfy the informational needs served on the Web.

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    0, but it also is immediately available.

    Data from the interactive sector of DW 2. 0 is available in an online manner. It is the norm for data to be accessible in an up-to-the-second basis in DW 2. Thus, if SOA requires up-to-the-second, online availability of data, then DW 2. 0 can supply that level of performance.

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    0 allows data to be found that otherwise would not be obvious or available at all. AWS Lambda, Azure Functions and Google Cloud Functions are all key offerings in the FaaS market. More and more businesses are adopting cloud systems or thinking about it.

    But cloud and hybrid cloud setups have pluses and.

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    0 and enterprise metadata – SearchDataManagement DW 2. 0 makes both structured and unstructured data available to SOA. Without the infrastructure that is built for DW 2.

    0, accessing unstructured data is very difficult, if not impossible, to accomplish. 0 also provides the basis for making the linkage between the structured and unstructured environments.

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    However, with granular data, DW 2. 0 can serve practically any request for information that can be generated by service-oriented architectures.

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