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The following products are currently available from The Information Difference store:Profiles White Papers Research Reports
Amalto and MDM - April 2008
Ataccama and MDM - August 2009
Cadis - August 2010
D&B Purisma and MDM - April 2008
Data Foundations and MDM - August 2009
Datanomic and Data Quality - May 2009
Exeros and MDM - April 2009
Experian QAS and Data Quality - August 2010
Golden Source and MDM - April 2008
Heiler and MDM - September 2008
Hybris and MDM - September 2008
IBM and MDM - August 2009
Initiate and MDM - August 2009
Kalido and MDM - August 2009
Netrics and Data Quality - May 2009
Oracle and MDM - August 2009
Orchestra Networks and MDM - April 2008
Pitney Bowes Software and Data Quality - May 2009
QAD and MDM - December 2008
Riversand - August 2010
SAP and MDM - April 2008
SAS and MDM - April 2008
Silver Creek Systems and Data Quality - April 2008
Siperian and MDM - August 2009
Stibo and MDM - April 2008
Sun and MDM - October 2008
Teradata and MDM - January 2009
Tibco and MDM - April 2008
Trillium Software and Data Quality - May 2009
Visionware and MDM - April 2008
To see a sample profile click here.
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How to get high quality master data
A paper by Cliff Longman published December 2009
The idea of “Six degrees of separation” is that any human being can be connected to every other human being through six relationships at most. Data is a little like this: through data relationships, all data is connected. When it comes to managing shared data (the primary focus of master data), you should plan to include all data types within your scope because, ultimately, it is all connected.
Cliff Longman has identified four different “strata” of data: transactional data (e.g. a payment is made), dependent data (e.g. sales regions), independent data (e.g. customer, product) and policy and reference data (e.g. categories of products, currencies) which have different characteristics. There are then four alternative strategies which ultimately end up with all shared data under management through a system of data mastering.
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The Master Data Management Endgame or
How I learned to stop worrying and love federation
A paper by Andy Hayler published April 2009
Master data management (MDM) has emerged as a key area of information management in the last few years. Initially much of the architectural debate was about whether to be data domain-specific or not. This paper argues that there is a second architectural dimension that has not had enough attention paid to it, and that is the one of a centralised versus federated approach to MDM.
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Mastering Data: Beyond Customer and Product
A paper by Andy Hayler published April 2008
The master data management (MDM) market has seen a battle of ideas over the last couple of years between "cross domain" approaches and specialist hubs for separate classes of master data, particularly "customer" and "product". In this new white paper Andy Hayler charts this battle and discusses the types of MDM architectures which play out in large enterprises.
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What’s the Link Between Data Governance and Success with MDM?
It has often been said that data governance is key to master data management (MDM), but is it? In this survey we wanted to get feedback from customers who have data governance activities and MDM projects, to see to what extent the two really are linked. In particular, we wanted to identify best (and worst) practice in data governance and MDM.
We conducted a survey, sponsored by Pitney Bowes Software, which was aimed at understanding better the views of businesses regarding their current data governance and MDM initiatives.
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Return on Investment (ROI) from Data Management Projects
Companies spend a lot of money on master data, data warehouse and data quality projects, but how successful are these initiatives in monetary terms? There is to date little information available relating to the return on these, often substantial, investments. In this survey, sponsored by Sand and Tibco, we explored how companies justify their expenditures, how they measure success, and how they assess their data management projects in monetary terms.
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Data Quality and MDM -
Currently, master data management (MDM) and data quality are treated as separate markets, yet any MDM project has a significant data quality component. Many authors have highlighted in the media the crucial importance of data quality initiatives to ensuring the success of MDM implementations. There is, however, little information on the approach being adopted by organizations that have implemented or plan to implement MDM.
We have therefore conducted a survey, sponsored by Informatica and Talend, aimed at understanding better the views of businesses regarding their current data quality and MDM initiatives.
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How Reliable is your Data Warehouse?
Data warehousing has been with us for almost three decades now. More than 25 vendors currently offer a wide range of approaches and software products dedicated to data warehousing. These range from packaged applications to cloud-
In the past, many data warehouse implementations gained the reputation of having a high failure rate, often delivering inconsistent data, with the consequence that businesses inevitably lost trust in their reliability. A root cause of this lack of reliability was that little or no attention was paid to ensuring the quality of the data loaded into the warehouse. Has the state of data warehousing in organizations improved over the past two decades?
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How Data Governance Links MDM and Data Quality
Many authors have recently highlighted in the media the crucial importance of data governance and data quality initiatives to ensure the success of MDM implementations. There is, however, scant information on the approaches being adopted by organizations that have implemented or plan to implement MDM, or indeed those who have chosen not to implement data governance.
We were therefore interested to explore the linkage between data governance, master data and data quality. In particular, to discover how organizations are tackling this area in practice. Additionally, we wanted to understand the scale, scope and success rates of data governance in relation to MDM and data quality initiatives in business. We have therefore conducted a survey into the link between data governance, MDM and data quality.
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The Link Between Data Warehousing and MDM
"Analytic MDM" has become established as one of the styles of MDM implementation adopted by businesses needing to effect a significant improvement in the speed and quality of their business reporting, often centered around one or more national, regional or enterprise data warehouses.
This is unsurprising since the "dimensions" of a data warehouse are essentially master data (e.g., hierarchies of products, customers, locations, etc.). Despite the close relationship between MDM and data warehousing, a glance at even the recent literature on these topics reveals that these two important areas tend to be treated as entirely separate. We have therefore conducted a survey into the link between data warehousing and master data management.
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Master Data Management Projects in Practice
Master Data Management (MDM) has received growing attention recently as an essential component of information management alongside data governance and data quality. Alongside this growth in interest in master data management, the provision of services for the implementation of master data management is featuring with increasing prominence in the portfolio of services offered by many Systems Integrators (SIs).
While many SIs currently claim or suggest they have extensive implementation expertise in master data management, there is little concrete information available regarding the use of systems integrators by end-
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The State of Data Quality Today
The topic of business data quality has been with us for decades. Given the large number of vendors offerings dedicated to resolving data quality (DQ) issues, one might be forgiven for believing that the problems have all but been resolved. A glance through the current literature reveals, however, that the problem of poor data quality is still very much alive.
Has the state of data quality in organizations improved over the past two decades? Or is data management, and data quality in particular, still in a ghastly state with organizations and senior management feeling that the problem is overwhelming? Despite the clear concerns from business and a plethora of software vendors, there is surprisingly little concrete information available regarding the state of data quality in business.
We have conducted a survey, sponsored by Pitney Bowes Business Insight and Silver Creek Systems, aimed at gaining deeper insight into the views of businesses regarding their current or planned data quality initiatives.
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Styles and Architectures for Master Data Management
Master data management (MDM) has emerged as a key area of information management in the last few years. Initially much of the architectural debate was about whether to be data domain-
At The Information Difference we believe it is important for both organizations and vendors to understand how MDM is generally being implemented, so as to gain insight into the underlying reasons for the approaches selected and the available experience to date. We have therefore conducted a survey aimed at gaining deeper insight into the views and plans of businesses regarding their current or planned MDM initiatives, focused on the styles and architectures adopted or planned to be implemented.
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Impact of the Financial Crisis on MDM and Data Quality Initiatives
The recent financial crisis has had widespread impact on both individuals and businesses. It is against this background that a number of comments have appeared in the media urging businesses not to be distracted from their current IT plans but to focus even more on the areas that will bring growth. It seems entirely likely that consulting firms will be faced with delayed or cancelled projects and many software vendors will experience a slowdown in orders. But will most businesses realize that Master Data Management (MDM) and Data Quality (DQ) initiatives hold the key to delivering improved business information and therefore that it makes sense to pursue these initiatives even against the current economic background?
At The Information Difference we have conducted a survey aimed at gaining greater insight into the views and plans of businesses regarding their current or planned MDM and DQ initiatives. The objective of the survey was to explore the views of businesses on the impact of the financial crisis and "credit crunch" on their current and future plans for implementation of MDM and DQ.
92 respondents completed the survey from all around the world, the majority from North America (57%) and Europe (31%). Most of the respondents were from companies having annual revenues greater than US $ 1 billion and represented a wide spectrum of industries.
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Adoption of Data Governance by Business
Data Governance is the process of establishing and maintaining cooperation between lines of business to establish standards for how common business data and metrics will be defined, propagated, owned and enforced throughout the organization. It is closely related to master data management (MDM), which is the management of data that is shared between computer systems, such as customer, product, asset, location or contract.
The Information Difference has conducted a survey into the take-
"The best survey I've seen on the topic to date" Jill Dyché, Partner, Baseline Consulting
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Growing Adoption of Master Data Management by Business?
Master Data is data that is shared between computer systems, such as customer, product, asset, location or contract. The management of this data is known as master data management (MDM). The mounting pressure on businesses to increase fiscal data compliance, accountability and transparency has driven a growing number of organizations to put a tentative toe into the waters of MDM. This has in part been fuelled by the explosion of publications in this area aimed at convincing businesses that the route to consistent business information lies in effective management of their master data. There is, however, scant concrete information relating to the motivation and adoption of MDM by business.
Against this background, The Information Difference has conducted a survey in April 2008 into the take-
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