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What is teradata in data warehousing?

Updated: 9/16/2023
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Teradata is a RDBMS system like Oracle or SQL Server but designed specifically for use in data warehousing. Data Warehouses contain extremely large amounts of data that normal RDBMS systems like oracle or sql server cannot handle comfortably. They may eventually be able handle the data but their performance may not be the best. Teradata is a system that is specifically designed for handling such extremely high volumnes of data.

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Q: What is teradata in data warehousing?
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Does data warehouse contain data?

Warehousing term is used whenever it is about something to be stored in great quantity with proper categorisation for easy accessibility in need; same applies for data warehouse. It only gets in dept in case of data; relevancy, timeliness and analysis followed by reporting are of prime importance. Source(s): http://bit.ly/153rq7v


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data warehouse A data warehouse is the main repository of an organization's historical data, its corporate memory. It contains the raw material for management's decision support system. The critical factor leading to the use of a data warehouse is that a data analyst can perform complex queries and analysis, such as data mining, on the information without slowing down the operational systems. data mining The development of computational algorithms for the identification or extraction of structure from data. This is done in order to help reduce, model, understand, or analyze the data. Tasks supported by data mining include prediction, segmentation, dependency modeling, summarization, and change and deviation detection. Database systems have brought digital data capture and storage to the mainstream of data processing, leading to the creation of large data warehouses.


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Data warehouse databaseDesigned for analysis of business measures by categories and attributesOptimized for bulk loads and large, complex, unpredictable queries that access many rows per table.Loaded with consistent, valid data; requires no real time validationSupports few concurrent users relative to OLTPOLTP databaseDesigned for real time business operations.Optimized for a common set of transactions, usually adding or retrieving a single row at a time per table.Optimized for validation of incoming data during transactions; uses validation data tables.Supports thousands of concurrent users.


What is the difference between Microsoft SSAS and SPSS?

Microsoft SSAS (SQL Server Analysis Services) and SPSS(Statistical Package for the social sciences) are two different software tools designed for different purposes. Let's discuss the differences between them. Microsoft SSAS is an analytical data engine provided by Microsoft as part of the SQL Server suite. It is used for creating and managing online analytical processing (OLAP). SSAS enables multidimensional and tabular data analysis and provides features for data modelling, data aggregation, and advanced calculations. It is typically used for business intelligence and data warehousing applications, allowing users to analyze large volumes of data and gain insights for decision-making. SPSS is a software package primarily used for statistical analysis and data management in social science research. It provides a comprehensive set of tools and techniques for data exploration, descriptive statistics, hypothesis testing, regression analysis, and more. SPSS offers a user-friendly interface that allows researchers to import data, perform statistical analyses, and generate reports or visualisations of the results. In summary, the main difference between Microsoft SSAS and SPSS is their primary purpose and functionality. SSAS is focused on creating OLAP cubes and data mining models for business intelligence and data warehousing, while SPSS is dedicated to statistical analysis and data management in social science research.

Related questions

What is tpump in teradata?

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Virtual seminar on data warehousing by keysoft solutions?

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