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THE DATA DOWNLOAD

As leaders in Enterprise Data Management and Business Intelligence, we pride ourselves on being able to deliver successfully on our projects as well as provide high-quality content to our readers.

Nancy Couture

Recent Posts

How Business - IT Partnerships Develop Operational Analytics

Nov 21, 2016 9:39:56 AM   Nancy Couture

Topics: Data Quality, Data Integration, Program Management, Blog

A great example of business and IT working together to innovate is in the development of operational analytics. As data volumes and frequency of data continue to increase, organizations have realized that it’s not enough to analyze their data – they must take action on it. 

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5 Tips for Leading Agile Data Management Development Teams

Aug 9, 2016 3:37:32 PM   Nancy Couture

Topics: Agile, Program Management, Blog

One of the principles behind the Agile Manifesto states:

The best architectures, requirements and designs emerge from self-organizing teams.

This is a key success factor in agile data management, whether the team is developing a traditional data warehouse or any other type of enterprise data management solution. 

Self-managing teams can be very effective due to the following factors:

  • Better, faster communication.
  • More trust between client and product team.
  • Less conflict.
  • Increased motivation.
  • Informed decision-making.


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Assess Before You Leap: The Value of Assessments

Jun 30, 2016 5:32:00 AM   Nancy Couture

Topics: Program Management, Blog, Project Management

As organizations strive to continue responding to market changes and opportunities, there is an increasing need for operational and strategic information to better support the business. Before committing to or starting work on a large Business Intelligence (BI) initiative, which is typically a significant investment, organizations are increasingly recognizing the advantages of conducting a program assessment.

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Building the Foundation for Sound Data Governance

Jun 8, 2016 5:06:00 AM   Nancy Couture

Topics: Data Governance, Business Intelligence, Blog

Second in a series of articles that describes foundational steps to enable agile data warehouse development. The first installment described how to develop a business conceptual model as a starting point. This article shows how to build a "grass roots" data governance capability that features broad business stakeholder involvement.

With the focus that companies have on everything “data” – analytics, reporting, dashboards, Big Data, predictive analytics, decision science and so on – data governance is also increasing in importance. A good data governance program gets business stakeholders involved in deciding on data definitions, and in supporting or sponsoring consistent data usage across an organization.

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Agile Innovations in Data Management

Jun 3, 2016 8:38:00 AM   Nancy Couture

Topics: Agile, Blog

A look at best practices learned while using agile development methodologies for enterprise data management solutions, including an enterprise data warehouse, data governance, data quality, integrated analytics and reporting. It starts with building a strong foundation, and then delving into additional innovative solutions leveraging what gets learned and continuously improving and expanding on it.

A successful agile data warehouse can speed the delivery of information to organizations. Ideally, initial raw data can be delivered to analysts quickly, then integrated into a formal enterprise data warehouse (EDW) for more robust and broad reporting in ensuing development cycles.

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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.

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How to Create & Lead Self-Managing Teams

May 17, 2016 8:30:00 AM   Nancy Couture

Topics: Program Management, Blog

Self-managing teams are vital in order to be truly successful in agile development. Here's how to encourage self-managing teams, and the benefits that can be achieved.

Earlier blogs describe the foundational steps that enable agile data warehouse development.

The next focus for setting yourself up for a best in class agile data warehouse environment is to develop and support self-managing teams.

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How to Implement a Robust Data Quality Solution

Apr 25, 2016 1:53:51 PM   Nancy Couture

Topics: Data Quality, Blog

Data quality is becoming a key concern for companies who rely on data on a daily basis. Without a purposeful data quality program, information becomes inconsistent and unreliable.


 


This first series of articles describe foundational steps that enable agile data warehouse development. My prior articles published thus far describe how to:

The next focus for setting yourself up for a best in class agile data warehouse environment is to develop a robust data quality solution.

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