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The Top Master Data Management and Data Governance Consultancies

Mar 2, 2020 3:18:17 PM   Datasource

Topics: Data Governance, Program Management, Blog, Master Data Management

A growing number of organizations are implementing master data management and data governance initiatives, but many lack the expertise to best set themselves up for success. That is fueling the growing market for MDM and data governance consultancies.

To help organizations in making the selection of an MDM partner, the MDM Institute compiled its list of the top MDM and data governance consultancies. Separate lists were prepared for the top consultancies in North America, in Europe, in Asia, and globally.

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Data Governance Framework

Jan 31, 2017 3:28:00 PM   Datasource

Topics: Data Governance, Program Management, Blog

Five Components of a Solid Data Governance Program

By: Datasource

Data Governance is a key component to any company that wants to leverage the full value of their data.  A solid Data Governance framework helps ensure quality, reduces risk, and establishes and reiterates best practices.

At Datasource Consulting, we look at Data Governance Programs as an evolution. We believe there are five critical elements to develop a solid framework for a Data Governance Program.

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Data Governance Challenges: Understanding the Problem

Jan 27, 2017 3:44:00 PM   Datasource

Topics: Data Governance, Program Management, Blog

Understanding the Problem

By: Datasource

As outlined in the first article of the series, Data Governance Framework: Five Essential Components of a Solid Data Governance Program, Data Governance is a key component for many organizations.  However, many companies don’t know where to start. At Datasource Consulting, we manage and build Data Governance Programs for many of our clients and frequently start by understanding the Data Governance challenges facing their organization.

(FYI – Would you like us to evaluate and fine tune your current Data Governance Program?  Please call us at 888-453-2624 or complete the form on our contact us page.)

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An Introduction to Lean BI

Jan 16, 2017 11:10:33 AM   Steve Dine

Topics: Business Intelligence, Program Management, Blog

What is Lean BI and its Purpose?

By: Steve Dine

I have yet to meet a BI team that has too little on its plate. In this article we will look at some of the drivers creating all this work and offer a set of principles that can be used to become more efficient and effective while still focused on delivering value. The main idea for this methodology evolved while leading a BI team for a leading medical manufacturer. We were frustrated by the amount of time spent maintaining our existing infrastructure and the number of features/data elements being added to the data warehouse that weren’t being utilized. During that time, the company was advocating Lean manufacturing principles and practices in our European divisions and there appeared to be some parallels to our situation. Our dabbling into Lean was the original root that grew into this concept.

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A Note About Teams

Jan 11, 2017 5:01:06 PM   Nancy Couture

Topics: Agile, Program Management, Blog

A Note About Teams: Team Formation & Your Role As a Leader

By: Nancy Couture

I'm writing a series of posts that discuss five tips for creating and leading agile data management development teams. My previous post focused on tip No. 1: "Hire 'A' Players and Empower Them." Before moving on to tip No. 2, I wanted to take a moment to discuss team dynamics.

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Successful Business Intelligence First Requires Defining “Success”

Dec 20, 2016 10:19:31 AM   Steve Dine

Topics: Business Intelligence, Program Management, Blog, ROI

Business Intelligence: Perception and Reality

By: Steve Dine

How many times have you heard a statistic such as "42% of respondents rate their Business Intelligence (BI) program as moderately successful" or "more than 50% of all Business Intelligence projects fail"? When I read these types of statistics I often wonder what's behind these numbers. I'd love to be able to drill down directly to the respondents and ask them how they defined success or failure when answering the question. I recently met with a company that asked if I could come in and help make their Business Intelligence program more successful. Naturally, my first question was to ask them how they define success. Each person in the room defined success a bit differently and meeting turned into a healthy discussion on what constitutes a successful Business Intelligence program.

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Business Intelligence Lifecycle Management

Dec 20, 2016 10:18:55 AM   Steve Dine

Topics: Program Management, Blog, BI Automation

An Introduction to Business Intelligence Lifecycle Management

By Steve Dine, Managing Partner - Datasource Consulting

It’s no secret that Business Intelligence* (BI) projects are both time consuming and resource intensive, often suffer from poor communication between the business and IT, and are usually inflexible to changes once development has started. This is due, in large part, to the method by which BI projects are traditionally implemented. Regardless of the methodology you employ, at the very least, a successful BI iteration requires:

  • Business requirements identification
  • Data analysis
  • Data architecture and modeling
  • Data integration (ETL, ELT, data virtualization, etc)
  • Front-end development
  • Testing and release management.

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Business Intelligence Projects Why They Fail (Part 1)

Dec 20, 2016 10:18:38 AM   Datasource Consulting

Topics: Business Intelligence, Program Management, Blog, Project Management

Business Intelligence Projects: Why They Fail (Part 1 of 5) - The Crumbling Foundation

For Business Intelligence projects (BI) to be successful, they must meet user requirements, be designed with strong user involvement, include a manageable scope, provide fast query response times, deliver the required reporting and analytic capabilities and provide value. Also, as nearly all experienced BI practitioners will attest, for business intelligence projects/programs to be successful, they must be built iteratively. In the trenches, that means sourcing, integrating, and developing front-end capabilities that target a subset of the enterprise data in each project. Sometimes the scope of an integration project is limited to a specific organizational process, such as invoicing, and other times by system, such as order-to-cash. Either way, subsequent business intelligence projects add to the scope and volume of data that is integrated and available for analysis. For initial business intelligence projects and subsequent iterations to be successful, the data architecture must be scalable, flexible, understandable and maintainable. However, most organizations put more thought and effort into their selection of BI tools than their data architecture. The end result is that they implement a data architecture that crumbles under the growing requirements of their users and data.

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Enterprise Data Management - Industry Terms

Dec 20, 2016 10:18:20 AM   Datasource Consulting

Topics: Business Intelligence, Program Management, Blog, Terms

Enterprise Data Management - Key Definitions of industry terms

At Datasource Consulting, it is fairly common that our friend and even some colleagues will ask us about some of the Enterprise Data Management terms we use on a regular basis.  It also seems that everyone is aware of how fast the Enterprise Data Management industry is moving and how quickly new terms pop up.

Below, you will find definitions to some of the Enterprise Data Management terms that we come across frequently and have a meaningful tie-in to the Business Intelligence and Data Integration space.

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Business Intelligence Industry Review and Trends for 2014

Dec 20, 2016 10:17:24 AM   Steve Dine & David Crolene

Topics: Data Security, Agile, Big Data, Data Quality, Data Integration, Program Management, Blog, Cloud, Master Data Management

Business Intelligence Industry: 10 Considerations for 2014

By:  Steve Dine and David Crolene

Each year, we reflect upon the business intelligence industry and enterprise information management (EIM) industry and provide a review of the noteworthy trends that we encounter in the field.  Our review emanates from five sources: our customers, industry conferences, articles, social media, and software vendors. This year has proved to be an interesting one on many fronts.  Here is our business intelligence  industry review and observations for 2013 and predicted trends for the remainder of 2014.

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