Category Archives: DataQuality
Customer & Supplier are Roles – But What Type?
Customer & Supplier are NOT Master Data Entities in Master Data Management (MDM). They are in fact Roles that can be played by the entity Third Party. But are there roles derivable or declarative, i.e. must they be declared and defined? Using the concept of declarative Roles allows unlimited number of Roles to be defined for any third party over time. Continue reading
Posted in DataQuality, Master Data Management
Tagged #MDM, #Role, #Supplier, #ThirdParty, Customer, DataQuality
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Data Quality: Objective or Subjective?
Data quality cannot be looked at and defined objectively unless you know the context in which it is to be applied, i.e. the Business Functions the data is meant to support. All other definitions are subjective and, as such, prevent Data Quality being achieved. Continue reading
Logical Data Model for Customer & Supplier
The logical data model below shows the data structure needed to support Customer, Supplier and Employee. Pardoxically, none of these appear as an enitity on model! How can that be? There is a very good reason for this, which is … Continue reading
Posted in DataQuality, Master Data Management
Tagged #MDM, #Supplier, Customer, DataQuality
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Customer is Not a Master Data Enitity.
Having Customer and Supplier as Master Data Entities is about as sensible as having Creditor and Debtor. Why? Because all of these terms refer to derivable relationships and implementing them as Master Data Entities is both a modelling and business … Continue reading
Will Best Practice Keep Your Data Quality Boat Afloat?
Some of attendees at a recent workshop that I ran told me that data quality was assured in their enterprise because they always followed industry best practice. On the surface this seems to be a compelling argument. If you are … Continue reading
Posted in DataQuality
Tagged Best Practice, Data Architecture, Data Structure, DataQuality, Structured Methods
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Data Quality: Driven by Function and Form or Glue and String?
Is the data quality in your enterprise driven by function and form or held together by string and glue? How did you map and build the data structures required to support the functions of the enterprise? Did you start with … Continue reading
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Data Quality: Dead Crows Kill Customers!
Dead Crows also Kill Suppliers! While recently doing a webinar on with Dylan Jones, of Dataqualitypro, I was the describing the essential role of Logical Data Model plays in Data Quality. During our discussions, Dylan asked me to give examples … Continue reading
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The Pitfalls of Data Re-Use
The reuse, though seemingly an eminently sensible practice, is fraught with danger. The only data that is truly safe to re-use is genuinely raw data. All other data should carry a health warning.
Read on on to find out what these dangers are and how to avoid them. Continue reading
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Name That Place
There is one aspect of Data Management and Data Quality that causes the greatest proliferation of duplicates across the globe, is the confusion that exists regarding the Unique Identifiers (UIDs) of data entities. I previously addressed UIDs in the posts … Continue reading
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Data Quality – One Version of the Truth?
The concept of “one version of the truth” is possibly the most widely discussed (and disputed) topics in Data Quality. Some say that it can never exist, others, that it must always exist or there is no quality. There is one version of the truth but, perhaps, not the truth as you know it! Know the Unique Identifier (UID) and the truth becomes blindingly obvious!
Click on “Read More” to see how. Continue reading
Posted in Data Structure Modeling, DataQuality
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