Agile Analytics: A Value-Driven Approach to Business - download pdf or read online

By Ken W. Collier

Utilizing Agile tools, you could deliver some distance larger innovation, worth, and caliber to any information warehousing (DW), enterprise intelligence (BI), or analytics undertaking. even if, traditional Agile equipment needs to be conscientiously tailored to deal with the original features of DW/BI initiatives. In Agile Analytics, Agile pioneer Ken Collier exhibits tips to just do that.

Collier introduces platform-agnostic Agile options for integrating infrastructures such as diversified operational, legacy, and distinctiveness platforms that blend advertisement and customized code. utilizing operating examples, he exhibits the right way to deal with analytics improvement groups with largely different ability units and the way to help huge, immense and fast-growing facts volumes. Collier’s options supply optimum worth no matter if your initiatives contain “back-end” facts administration, “front-end” enterprise research, or both.
Part I makes a speciality of Agile undertaking administration ideas and supply workforce coordination, introducing middle practices that form the way in which your Agile DW/BI undertaking group can collaborate towards success
Part II offers technical tools for allowing non-stop supply of commercial worth at production-quality degrees, together with evolving more suitable designs; test-driven DW improvement; model regulate; and undertaking automation
Collier brings jointly confirmed recommendations you could observe correct now—whether you’re an IT decision-maker, information warehouse expert, database administrator, enterprise intelligence expert, or database developer. together with his aid, you could mitigate venture chance, increase enterprise alignment, in attaining higher results—and rejoice alongside the best way.

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Additional info for Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing (Agile Software Development Series)

Sample text

In fact, there are many different Agile development flavors that add valuable principles and practices to the broader collective known as Agile development. 5 Each is guided by the core values expressed in the Agile Manifesto. Agile Analytics is an adaptation of principles and practices from a variety of these methods to the complexities of data-intensive, analytics-based systems integration efforts like data warehousing and data mart development. Simply iterating. Short, frequent development iterations are an essential cornerstone of Agile development.

Such an approach must place the responsibility of success equally on the users, stakeholders, and developers and should reward a team’s ability to adapt to new directions and substantial requirements changes. WHY DO WE NEED AGILE A NALYTICS ? 19 As we observed earlier, most classes of project failure are user-satisfactionoriented. If we can continuously adapt the DW/BI system and align with user expectations, users will be satisfied with the outcome. In all of my past involvement in traditional DW/BI implementations I have consistently seen the following phenomena at the end of the project: Users have become more educated about BI.

Moreover, relational data modelers may not have dimensional modeling expertise and vice versa. ETL development. ETL refers to the extraction of data from source systems into staging, the transformations necessary to recast source data for analysis, and the loading of transformed data into the presentation repository. ETL includes the selection criteria to extract data from source systems, performing any necessary data transformations or derivations needed, data quality audits, and cleansing. Data cleansing.

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Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing (Agile Software Development Series) by Ken W. Collier


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