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

Agile Analytics: A Value-Driven Approach to Business Intelligence and Data Warehousing Ken W. Collier ebook
Publisher: Addison-Wesley
ISBN: 032150481X, 9780321504814
Format: pdf
Page: 366

See the book The Analytical Puzzle: Profitable Data Warehousing, Business Intelligence and Analytics (ISBN 978-1935504207) for details. May 26, 2011 - Using Agile methods, you can bring far greater innovation, value, and quality to any data warehousing (DW), business intelligence (BI), or analytics project. Jul 27, 2010 - There is no standard definition of BI, though IDC New Zealand senior market analyst Louise Francis groups BI into two categories — performance management tools and applications; and the data warehouse platform. 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. The end goal is to Getting a self-service business intelligence environment may be as easy as linking to a single database or as complex as building data warehouses and data marts. Jun 7, 2010 - Given the growth of data in enterprises, 'Divide & Conquer' is a good data management strategy, where data assets in an organization are managed based on how information is to be extracted & used. While writing SQL is one approach to getting answers, it does not suit all levels of skills and experience. VG- brief comment- agile vs adaptive. May 7, 2014 - Supporting the analysts, my team has built a MySQL data warehouse that pulls all the data from our enterprise resource planning software (hereafter ERP; we use Netsuite) with 30-minute latency and exposes those data in a simpler, "People want to move from a culture of reporting to a culture of analytics" - Steffin Harris. €�End-user BI tools are split into two categories: Query, Reporting, Analysis Tools [QRA] being dashboards, production monitoring, ad hoc queries and so on; and Advanced Analytics, predictive analytics such as data mining and statistics,” she says. It all depends This allows the business to be more agile, adaptable and efficient. One potential downside to a subject area or source base approach is trying to implement without strong architectural and modeling guidelines in place. To me, embedded BI is one way of managing data I foresee the usage of embedded BI primarily for operational analytics while data warehousing and other forms of data management will continue to play its role for strategic BI. Dec 2, 2013 - Self-service business intelligence (SSBI) is an approach to data analytics that enables business users to access and work with corporate information without the IT department's involvement. Providing decision-support data that is consistent, integrated, standardized, and easy to understand. 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. Mar 6, 2011 - Agile may deliver value to customers faster, and may be more cost effective, but can it work for Business Intelligence and Data Warehouse projects? Ben Harden, PMP, is a Managing Director in the Data Management and Business Intelligence practice of the Richmond, Virginia based consulting firm CapTech . 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.