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

On the other hand, when the business users control their own data and BI, they can be much more agile and thus able to glean more value from their data, faster. There is also a strong predisposition and Business users generally conceive of BI as computer-based techniques used in recognizing and analyzing business data for decision-making in the organization. €�We moved so far away from agile, it wasn't even funny,” she said. Still, it's worth noting the cloud BI option? May 19, 2014 - To fully detect, isolate, and resolve quality issues in a traditional, large-scale data warehouse requires that several approaches be used together. See the book The Analytical Puzzle: Profitable Data Warehousing, Business Intelligence and Analytics (ISBN 978-1935504207) for details. Jul 24, 2013 - Oracle and IBM also have a similar market approach; they both have downloadable software to connect their other database and analytics products to data stored in Hadoop. Sep 21, 2013 - Hadoop has evolved as a heterogeneous enterprise data warehouse for optimized modeling, deployment, and management. Nov 12, 2013 - As a proponent of agile data warehousing and business intelligence, I am constantly looking for new techniques for delivering value to customers faster, adapting to their feedback, and evolving toward the right business solutions It isn't about data warehousing, BI, or analytics … or is it? The key is to take a risk-based approach. A common architectural approach for transactions and analytics Cloud-Based, Real-Time Analytics. 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. Providing decision-support data that is consistent, integrated, standardized, and easy to understand. Aug 23, 2012 - In actual use, however, the KPI, its use and its value have been dumbed down in ways that diminish the quality of intelligence we gain from using business analytics. Oracle and IBM all at the same time. Kopp, whose background is in business intelligence, said she realized that all her presentations to customers were more about workload management instead of getting value from their data. 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. My clients routinely tell me stories about building dozens of BI reports based on customer spreadsheets or requests, only to discover that most of these are rarely or never used. Huge range of access points, applications, workloads, and data sources for any future Hadoop data warehouse demands an architectural flexibility that traditional data warehouses, with their operational business intelligence (BI) focus, . Sep 19, 2011 - For example, the huge amount of data available today – both structured and unstructured – requires a “divide and conquer” approach to data warehouse and BI projects as well as engaging across the functions and departments of organizations.