Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing . Ken W. Collier

Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing


Agile.Analytics.A.Value.Driven.Approach.to.Business.Intelligence.and.Data.Warehousing..pdf
ISBN: 032150481X,9780321504814 | 366 pages | 10 Mb


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Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing Ken W. Collier
Publisher: Addison-Wesley




Today, agile is For example, an insurance company moved to an agile development process for all business analytics projects, adopting techniques such as paired programming, story walls and test-driven development. There is first the difference in Both propose Star Schema Datamarts, business driven incremental development involving prototyping iterations (Agile) and report/query delivery from relational databases directly or via OLAP data repositories such as n-dimensional cubes. Mar 18, 2014 - For years, many organizations had development shops that leveraged agile methods and practices for development projects other than data projects like business intelligence. While I found it interesting, there's a lack of rigor in the analysis that is a common problem when using surveys at many companies- misinterpreting trends from surveys based on small sample sizes. May 19, 2014 - But it's not a case of either/or: the majority of those who've either already adopted cloud BI or are intending to do so are using the SaaS system to complement their existing BI and analytics capabilities. The key is to take a risk-based approach. Still, it's worth noting the cloud BI option? Sep 11, 2013 - In Forrester's Forrsights Strategy Spotlight: Business Intelligence And Big Data, Q4 2012 survey of 634 BI users and planners, we found that social and mobile data is actually a pretty low priority: We wrote about big data hubs in our report, Deliver On Big Data Potential With A Hub-And-Spoke Architecture, and indeed we think most firms will shift from a data-warehouse-centric approach to one that favors low-cost data hubs. Jul 2, 2013 - Based upon my experience, I can name at least nine data components that need testing and validation in a business intelligence project. VG- brief comment- agile vs adaptive. From a data warehousing perspective, Amazon Redshift has really opened up the possibilities and a new breed of analytics providers is disrupting the old guard. Dec 29, 2013 - In my opinion, it points back to visual analytics, dedicated teams of business analysts with clear missions and good data management and warehouse practices with an agile approach, so that major misses can be caught, reviewed and corrected mid-course. Figure 1 Business Intelligence & Analytic Data Components. Aug 17, 2013 - In your choice for a BI and Data warehouse applications and a comparison of vendors it is important to know what the goal is for your BI Data Warehouse.