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SELECT list is the list of columns or SQL expressions to be returned by the query. This is approximately the relational algebra projection operation. AS optionally provides an alias for each column or expression in the SELECT list. This is the relational algebra rename operation. FROM specifies from which table to get the data. [3]
In situations where the number of unique values of a column is far less than the number of rows in the table, column-oriented storage allow significant savings in space through data compression. Columnar storage also allows fast execution of range queries (e.g., show all records where a particular column is between X and Y, or less than X.)
SAP HANA Information Modeling (also known as SAP HANA Data Modeling) is a part of HANA application development. Modeling is the methodology to expose operational data to the end user. Reusable virtual objects (named calculation views) are used in the modelling process.
Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.
Multidimensional Expressions (MDX) is a query language for online analytical processing (OLAP) using a database management system. Much like SQL , it is a query language for OLAP cubes . [ 1 ] It is also a calculation language, with syntax similar to spreadsheet formulae.
The Current_Flag value of 'Y' indicates the current tuple version. Transactions that reference a particular surrogate key (Supplier_Key) are then permanently bound to the time slices defined by that row of the slowly changing dimension table. An aggregate table summarizing facts by supplier state continues to reflect the historical state, i.e ...
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OLAP clients include many spreadsheet programs like Excel, web application, SQL, dashboard tools, etc. Many clients support interactive data exploration where users select dimensions and measures of interest. Some dimensions are used as filters (for slicing and dicing the data) while others are selected as the axes of a pivot table or pivot chart.