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

Oct 7, 2011 - The Best People in Data Warehousing and Business Intelligence Agile Business Intelligence principles are based on its cornerstone of small, quick iterations focusing on value at each cycle and building quality solutions in a time-boxed way, seems to be the right fit to deliver information management Team problems adopting the approach where they think they are doing the right thing but for some reason they cannot tell why Agile is still not working for them. SAP Lumira delivers agile visualizations for business analysts to uncover more insight from their data – big and small – in SAP HANA and contribute new information. 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. Sep 26, 2013 - Many teams who follow this approach end up building massive data warehouses that can take months – or years – to complete before anything is delivered to the end-users. Oct 17, 2013 - The other day the TDWI (the Data Warehouse Institute) sent me a brochure highlighting Agile BI workshops and seminars. None of these approaches/disciplines can be advantageous if you can't adapt based on the information they provide. Feb 28, 2013 - Unique to Birst is its powerful, integrated approach to business analytics, which automates many of the traditional steps common to business intelligence solutions. Were supposed to do, Big Data is supposed to help organizations improve business performance and gain competitive advantage. 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. Nov 5, 2013 - The need for detailed requirements gathering, data quality and cleansing work is paramount in launching any business intelligence project. Nov 11, 2013 - While other vendors look to consolidate and lock in their stacks, SAP takes an open approach to innovation and allows a wide variety of partners to build and deliver solutions – including analytics – on SAP HANA. Is this just another Or is there something here that uniquely addresses real operational and strategic issues in the increasingly performance-driven and customer-focused business of higher education? Adaptation These organizations will not see the degree of benefit from data analytics as more adaptable, agile ones. Dec 12, 2012 - Meanwhile a wide range of UK institutions and shared services have identified business benefits in analytics and activity data through project work in the Jisc Activity Data, Business Intelligence and Customer Relationship Management programmes. 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. Dec 30, 2011 - I am currently reading a book by Ken Collier, called “Agile Analytics, A Value-Driven Approach to Business Intelligence and Data Warehousing”. Here's how they Ongoing scoping, rapid iterations that deliver working components, evolving requirements, scrum sessions, frequent and thorough testing, and business/development communication are important facets of a formal agile approach. " A good example of this is Tableau (which markets itself as "visual analytics for everyone"). Jan 3, 2013 - Much like decision support, data warehousing, business intelligence etc. VG- brief comment- agile vs adaptive.