Ensuring Speed, Flexibility and Agility with Self Service Analytics

29 March, 2018

Patricia L. Saporito

Data Warehousing

Introduction Today’s digital world and fast paced business environment demands pervasive, timely analytics. Organizations must deliver speed, agility and ease of use for data access and analytics. In response, business intelligence (BI) and analytics teams are shifting to a more agile, self-service model that enables greater user access to data and the ability to create and perform individualize

Improving the ROI of Big Data and Analytics through Leveraging new Sources of Data

05 March, 2018

Bart Baesens

Data Warehousing

Investing in new sources of data can help to unravel complex customer behavior and improve key analytical insights Introduction Big Data and Analytics are all around these days. Most companies already have their first analytical models in production and are thinking about further boosting their performance. Far too often, they focus on the analytical techniques rather than on the key ingredient: d

Building a Rock Solid Data and Analytics Strategy

27 September, 2017

Patricia L. Saporito

Analytics

Every organization’s analytics strategy should be connected to its data strategy; and every organization should have a data strategy that supports its business strategy Introduction Like the lyrics in the children’s song Dem Bones, “the hip bone’s connected to the thigh bone”, your data strategy is connected to your analytics strategy – or it should be! Further, your analytics strategy

Challenges of Data Warehouse Re-Architecture

21 July, 2017

Bruce D. Johnson

Data Warehousing

Data warehouse / business intelligence / analytics environments require business and IT cooperation for successful architecture and design Introduction In working with many large corporations across a variety of industries, it is clear that we all face the reality of re-architecting data warehouses, whether we want to admit it or not. Since data warehouses are business driven (rethink your strateg

Data Warehouse Standards

23 February, 2017

Sid Adelman

Data Warehousing

New

Standards are different from guidelines.  Standards are firm and must be followed.  Successful data warehouses use standards Introduction Many dog owners give their dogs what they consider to be commands.  They are really more like guidelines. ("Boscoe come!… pause, pause, pause…  Well I guess Boscoe is busy with his chewy toy and doesn't want to come just now.") A number of organizations

Increasing the Business Value of Business Intelligence

01 October, 2010

Mark Mosely

Data Warehousing / Business Intelligence / Analytics

Organizations can find increased value in business intelligence and analytics efforts through the use of various data delivery strategies. Introduction Like many organizations, your company probably has invested significant time, effort, and money into establishing your data warehousing and business intelligence environment.  You’ve built the databases and the ETL programs to move, clean and in

Foundations of Data Warehousing

20 March, 2015

David Marco

Data Warehousing

Data warehousing is the proven architecture for delivering subject-oriented, stable, analytical information for decision making.  Effective data warehouse development provides many business benefits. Introduction A data warehouse is an enviroment that combines an integrated decision support database with software to collect, cleanse, transform, and store data from a variety of operational and ext

Agile Framework for Managing and Measuring Enterprise Business Intelligence

01 October, 2008

Karthikeyan Sankaran

Data Warehousing

To be agile, business intelligence and analytics systems need frameworks and metrics to enable stable evolution. Introduction Enterprise Business Intelligence and analytics solutions are complex implementation efforts because of the Develop – Support (Growth-Sustain) cycles followed concurrently. Every enterprise wide BI system continuously evolves over a period with new business functionality

Dimensional Data Modeling Fact Qualifier Matrix

01 October, 2008

Pete Stiglich

Data Warehousing

Fact Qualifier Matrix capabilities can be expanded to improve the value of conformed dimensions in business intelligence and analytics systems Introduction The venerable Fact Qualifier Matrix (FQM) has been a tool long used for demonstrating for dimensional models how fact and dimension tables intersect to ensure that dimensional models are conformed. A key principle of dimensional modeling is th

Performance Benefits of Surrogate Keys in Dimensional Models

01 April, 2007

Pete Stiglich

Data Warehousing

There are many benefits to implementing surrogate keys in a dimensional model design for a data warehouse data model Introduction There are many reasons for implementing surrogate keys in Dimensional Models (enterprise data modeling) such as insulating dimensions from changes to source systems and enabling historical versioning of dimension members. However, query performance in the data warehouse