what describes contents of a data warehouse
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Metadata â data about data describes the contents Unformatted text preview: Metadata – Data about data ; describes the contents of a data warehouse, its structure (such as field name, data type, default value, length), meaning, syntax and the manner of its use. Ex: Design view in Access or SQL view. CASE 2.2 Test Q: What is the example of Metadata? – Number , revenue….
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- The physical structure of the data store consists of the Active Directory database file (Ntds.dit) and its associated log and temporary files. The data that is held in the database file includes both static data and dynamic data. The following figure illustrates the physical structure of the data store.
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What is Enterprise Data Warehouse What is Enterprise Data Warehouse. Enterprise Data Warehouse is a centralized warehouse which provides service for the entire enterprise. A data warehouse is by essence a large repository of historical and current transaction data of an organization. An Enterprise Data Warehouse is a specialized data warehouse which may have several interpretations.
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- Data are the principal resources of an organization. Data stored in computer systems form a hierarchy extending from a single bit to a database, the major record-keeping entity of a firm. Each higher rung of this hierarchy is organized from the components below it.
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metadata Metadata is data that describes other data. Metadata summarizes basic information about data, which can make finding and working with particular instances of data easier. For example, author, date created and date modified and file size are examples of very basic document metadata.
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- This definition is stored in the DBMS catalog, which contains information such as the structure of each file, the type and storage format of each data item, and various constraints on the data. The information stored in the catalog is called meta-data, and it describes the structure of the primary database.
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What is Data Repository A database warehouse is one large Data Repository of all business related information including all historical data of the business organization implementing the data warehouse.
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- And I believe actual data inserted into table is not part of schema. Schema describes what data, where and how can be stored, accessed, etc. Data itself is stored in tablespace and is not part of user's schema. Quota on that tablespace is data about user and is stored in dictionary, so it is schema object. So schema is not a data container. Schema is rules, properties, definitions, but not rows in the table.
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- A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. A data warehouse is a central repository for all or significant parts of the data that an enterprise's various business systems collect. SearchSQLServer Search the TechTarget Network
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- SQL Data Warehouse offers guaranteed 99.9 percent availability, regulatory compliance, advanced security features, and tight integration with upstream and downstream services so you can build a data warehouse that fits your needs. SQL Data Warehouse is the first service enabling enterprises to replicate data virtually anywhere around the globe.
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- Normally, the data in data warehouse is not supposed to be updated only inserts should happen into data warehouse. Ideally, the current data should become part of data warehouse, after some pre-decided time period, after which it will only be used for analysis purpose and not for transactions.
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- An attribute-value system is a basic knowledge representation framework comprising a table with columns designating attributes (also known as properties, predicates, features, dimensions, characteristics, fields, headers or independent variables depending on the context) and rows designating objects (also known as entities, instances, exemplars, elements, records or dependent variables).
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- The attributes in all the levels are mapped to different columns in a single table called PRODUCT. The snowflake schema represents a dimensional model which is also composed of a central fact table and a set of constituent dimension tables which are further normalized into sub-dimension tables. In a snowflake schema implementation, Warehouse Builder uses more than one table or view to store the dimension data.
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- A data warehouse is a federated repository for all the data that an enterprise's various business systems collect. The repository may be physical or logical. Download this free guide
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- What the Warehouse Contains. This document describes how data in the Warehouse is organized and explains table and data element terminology. The Warehouse contains data from transaction systems. The information from each transaction system is referred to as a data collection.
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Data Warehouse (DW) Data Warehouse (DW) Definition - What does Data Warehouse (DW) mean? A data warehouse (DW) is a collection of corporate information and data derived from operational systems and external data sources. A data warehouse is designed to support business decisions by allowing data consolidation, analysis and reporting at different aggregate levels.
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WAREHOUSING AND WAREHOUSE MANAGEMENT Warehouse functions include: the storage of goods to permit managing product flow or to accommodate longer production runs; Growth of Warehousing 1997–2002. Warehousing and Storage. Source: U.S. Department of Commerce: Department of the Census: Economic Census.
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Difference Between Database and Data Warehouse A data warehouse is a special type of database used for analysis of data. A general database is usually used for transaction processing, and hence, it is not optimized for analysis and reporting. But a data warehouse is specially designed and optimized for analysis tasks.
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- Share to: A data warehouse system is just a database that provides a single-point of access to multiple ERP systems (ERP = software systems used by companies). The different ERP will be … interfaced to the data warehouse so that the data can be stored and shared by multiple ERP in a single point.
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Database Design Data about subjects must be organized in such a way that it provides a unified, overall picture of all the important details about the subjects over time. Data warehouses are the most common example. Data marts are subsets of data warehouses designed to support a part of an organization. Business rules.
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LDAP Basics As I mentioned, data stored in LDAP is stored in objects. These objects contain a number of attributes, which are basically a set of key/value pairs. Because data in LDAP is structured, objects can only contain valid keys, and which keys are valid is dependant on what class the object is.
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Explain the functions of Warehouse Suppliers will ship truckloads of products to the distribution center. The distribution center will then store the product until needed by the retail location and ship the proper quantity. Basic Functions of a Warehouse Basic function of a warehouse are movement of goods storage of goods, and information management. 1. Storage of Goods: One of the traditional requirements of a warehouse has been for storing goods.
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Aggregate (data warehouse) Aggregates are sometimes referred to as pre-calculated summary data, since aggregations are usually precomputed, partially summarized data, that are stored in new aggregated tables. When facts are aggregated, it is either done by eliminating dimensionality or by associating the facts with a rolled up dimension.
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Diving into Azure SQL Data Warehouse Data stored in a regular Azure Storage Account (either Page Blob or Block Blob) can also be queried or imported into Azure SQL Data Warehouse. Supported file formats include delimited text, Hive RCFile or Hive ORC file formats.
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Aggregate (data warehouse) From Wikipedia, the free encyclopedia. Aggregates are used in dimensional models of the data warehouse to produce dramatic positive effects on the time it takes to query large sets of data. At the simplest form an aggregate is a simple summary table that can be derived by performing a Group by SQL query.
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What is Meta data, Master data and Transaction data in SAP ? What is Meta data, Master data and Transaction data in SAP ? Meta Data: Meta Data is the information about Data. It gives the information about structure of data or MetaObjects. Master Data: This Data is key business information like Customer information ,Vendor information, Employee , Materials etc. This is more like a reference data.