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THE DATA DOWNLOAD

As a business intelligence consulting company, we pride ourselves on being able
to deliver on our projects as well as provide good quality content to our readers.

4 Steps to High Impact Requirements Analysis

Jan 25, 2017 3:29:51 PM   Datasource Consulting

Topics: Blog, team, Business Intelligence, Data Warehousing

Why are Business Requirements Important to BI and Data Warehousing Projects?


By: Datasource Consulting

When considering a Business Intelligence (BI) and Data Warehousing project, it’s extremely important to not overlook the process of gathering, prioritizing, and agreeing on the project’s business requirements. This process of discovery is done after the company’s business objectives are documented, validated and organized by each functional business area.

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Amazon Redshift Tips & Tricks

Dec 20, 2016 10:20:00 AM   Chun Wu

Topics: Blog, Data Warehousing, Amazon Redshift, Cloud

Amazon Redshift Tips & Tricks:  Top 10 Tips & Tricks for Using Amazon Redshift


By: Chun Wu

Last month’s webinar, Working with Redshift: Amazon’s Affordable MPP Analytic Database in the Cloud, was well received and sparked a lot of interest from viewers.  Based on the feedback, interaction and questions received, Chun Wu was happy to create a more in depth level of Tips & Tricks for our Analytic Minute readers.

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No One Likes a Monday Morning Data Architect: 7 Steps to Avoid the Data Warehouse Hangover

Nov 21, 2016 9:18:36 AM   DeVon Doman

Topics: Data Architecture, Data Warehousing, Blog

Many consultants have come across unexpected data conditions while deep into the development or testing phase of a data integration effort. Unfortunately, the need for a major shift in architecture or approach is sometimes identified soon after a system is implemented into production. Upon discovering this type of situation, you likely experience a sinking feeling, knowing the potential negative consequences. You imagine blown budgets, missed deadlines, loss of credibility with the business, and unpredictable results. You begin analyzing what caused the problem, how it could have been avoided, and who is at fault

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Customer-Centric Data Driving Growth for Credit Unions

Jun 2, 2016 9:29:41 AM   Datasource

Topics: Data Warehousing, Blog, Program Management

Why you need a modernized data warehouse and BI environment and what it looks like

Most credit unions grew up in an era where custom-built data environments reigned supreme. Excel, SQL, and Microsoft Access were the workhorses of the data warehouse. Everything from member data to transaction data were tracked across multiple applications and spreadsheets. What started out as a solution for data to a handful of users was expanded and layered upon overtime, becoming unwieldy and inefficient  

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Building the Foundation With a High-level Architecture

May 30, 2016 8:30:00 AM   Nancy Couture

Topics: Data Warehousing, Blog, Data Architecture

This is the third in a series of articles describing foundational steps to enable agile data warehouse development. This first series of articles describe foundational steps that enable agile data warehouse development – something that has been a challenge in enterprise data management for years. My prior articles published thus far describe how to develop a Business Conceptual Model as a starting point, then building a “grass roots” (at a minimum!) Data Governance capability.

The next focus for setting yourself up for a best in class agile data warehouse environment is to develop a high level data flow architecture that is inherently flexible and leverages repeatable design patterns.

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How to Test for a Best-In-Class Agile Data Warehouse Environment

May 20, 2016 8:30:00 AM   Nancy Couture

Topics: Agile, Data Warehousing, Blog

Having a solid testing strategy and tool set is a foundational part of enabling agile data warehouse development. This article describes an approach that ensures solid testing that can be done efficiently and effectively in an agile development environment.

This is the first in a series of articles that describe foundational steps that enable agile data warehouse development – something that has been a challenge in enterprise data management for years. My prior articles published thus far describe how to develop a business conceptual model as a starting point, building a “grass roots” (at a minimum) data governance capability, and developing a high level data flow architecture.

The next focus for setting yourself up for a best in class agile data warehouse environment is to develop a solid testing approach and tools before actual development begins.

Read More