By Ken W. Collier
Utilizing Agile tools, you could convey a ways larger innovation, worth, and caliber to any information warehousing (DW), enterprise intelligence (BI), or analytics venture. even though, traditional Agile tools has to be conscientiously tailored to deal with the original features of DW/BI initiatives. In Agile Analytics, Agile pioneer Ken Collier exhibits the way to just do that.
Collier introduces platform-agnostic Agile suggestions for integrating infrastructures which includes assorted operational, legacy, and strong point structures that blend advertisement and customized code. utilizing operating examples, he exhibits the right way to deal with analytics improvement groups with generally diversified ability units and the way to aid huge, immense and fast-growing facts volumes. Collier’s suggestions provide optimum worth no matter if your initiatives contain “back-end” info administration, “front-end” company research, or both.
Part I makes a speciality of Agile venture administration suggestions and supply group coordination, introducing middle practices that form the best way your Agile DW/BI undertaking group can collaborate towards success
Part II offers technical tools for permitting non-stop supply of commercial price at production-quality degrees, together with evolving more suitable designs; test-driven DW improvement; model regulate; and undertaking automation
Collier brings jointly confirmed options you could practice correct now—whether you’re an IT decision-maker, info warehouse specialist, database administrator, company intelligence professional, or database developer. together with his support, you could mitigate venture danger, increase enterprise alignment, in achieving greater results—and celebrate 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)
He continues to refine these ideas as a technical lead and project manager on several Agile DW/BI project teams. Ken also frequently trains data warehousing and business intelligence teams in Agile Analytics, giving him the opportunity to exercise this approach with various technologies, team dynamics, and industry domains. S. and international conferences, including multiple TDWI (The Data Warehousing Institute) World Conferences as well as HEDW (Higher Education Data Warehousing) annual conferences.
There is no ability to expand. The data and/or reports are poor. The project is not cost-justified. Management does not recognize the benefits of the project. In other words, simply completing the technical implementation of a data warehouse doesn’t constitute success. Take another look at this list. Nearly every situation is “customer”-focused; that is, primarily end users determine whether a project is successful. There are literally hundreds of similar evaluations of project failures, and they exhibit a great deal of overlap in terms of root causes: incorrect requirements, weak processes, inability to adapt to changes, project scope mismanagement, unrealistic schedules, inflated expectations, and so forth.
Com/surveys/. WHY DO WE NEED AGILE A NALYTICS ? 21 adapted from those of our software development colleagues who have been maturing these practices for the past decade or longer. Unfortunately, the specific practices and tools used to custom-build software in languages like Java, C++, or C# do not always transfer easily to systems integration using proprietary technologies like Informatica, Oracle, Cognos, and others. Among the problems that make Agile difficult to apply to DW/BI development are the following: Tool support.
Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing (Agile Software Development Series) by Ken W. Collier