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The Ownership Guide also explains how the sources are used and also has a full list of the Information Providers used. The choice for the data listed as ownership (for each month) depends on the sources. Bureau van Dijk uses many sources for the Shareholder type data and the main sources include: Also included is information on Source Identity and Date of Info. Information on shareholders includes data like: type, percentage direct ownership, total percentage ownership, country, etc. Allthough this makes it easier to view the history of ownership, if many changes occur in each year this makes interpreting the data not always easier: This option presents the recorded shareholders in columns by year. At the top the current shareholders are listed and below this the previous shareholders: The first option presents a long list of all recorded data in the database. There are two presentation options for the Shareholder data: The only way to view the full historical data for the current and previous shareholders for companies, is using the Ownership Data option that appears in the menu (on the right side of the screen) when you call up the basic Snapshot on a company from your results list by clicking on the name. If you need these types of companies or a Global geographical coverage you could go for a database like Orbis or Bankscope. Amadeus does not include financial type company data like Banks or Insurance companies.

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If your license / subscription includes the ownership module the information is available for European companies of the industrial type. In a previous post I mentioned how you could find out how the types of shareholders could be identified using the codes.

Warning: WRDS and Two-Factor AuthenticationĪ database like Amadeus (from Bureau van Dijk) has shareholder data that can go back to 2002.

TruCost ESG data from Compustat (Capital IQ).

CRSP US Indices will start using the UES classification.Path JSON Path to identify attributes in a data item.Ĭoncept role The role of a Category:Data model concept in the tree structure of a data model.ROOT: Root concept in a data model, i.e., no parent concepts.NODE: Structure concepts in a data model, i.e., parent and child concepts.LEAF: Leaf concept in a data model, i.e., no child concepts, provides the effective data values. for several address types in a data model. Allows re-use of data type concepts, e.g. 1 instance related to its parent.EXACTLY_ONE: Exactly 1 instance related to its parent.ZERO_OR_MORE: Optional, multiple instances related to its parent may exist.ONE_OR_MORE: Mandatory, multiple instances related to its parent may exist.ĭata type Data type of a data model concept, i.e., ARRAY, BOOLEAN, DATE, ENUM, INTEGER, OBJECT, or STRING.Ĭoncept type Complex data type of a data model concept, defined by another data model concept. Parent concept Hierarchical relation between two concepts of a data model, e.g., the CDQ Data Model.Ĭardinality Cardinality of data model concepts.ZERO_OR_ONE: Optional, but max.

These keys are unique in the CDL context.

data model concepts can be referenced in a technical integration context. Technical key Defines a unique key by which e.g. Part of Hierarchical relation between two concepts of the CDQ Data Model. a country-specific language.ĭescription Informal and comprehensive human-readable definition of a concept.Įxample A simple example supporting the understanding of a concept, business rule, etc. In contrast to terms, the name does not depend on a given context, e.g.

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