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BigQuery is a managed, serverless data warehouse product by Google, offering scalable analysis over large quantities of data. It is a Platform as a Service that supports querying using a dialect of SQL. It also has built-in machine learning capabilities. BigQuery was announced in May 2010 and made generally available in November 2011. [1]
Create/alter table: Yes - can create table, alter its definition and data, and add new rows; Some - can only create/alter table definition, not data; Browse table: Yes - can browse table definition and data; Some - can only browse table definition; Multi-server support: Yes - can manage from the same window/session multiple servers
Snapshot fact tables record facts at a given point in time (e.g., account details at month end) Accumulating snapshot tables record aggregate facts at a given point in time (e.g., total month-to-date sales for a product) Fact tables are generally assigned a surrogate key to ensure each row can be uniquely identified. This key is a simple ...
In the context of SQL, data definition or data description language (DDL) is a syntax for creating and modifying database objects such as tables, indices, and users. DDL statements are similar to a computer programming language for defining data structures, especially database schemas. Common examples of DDL statements include CREATE, ALTER ...
The term "schema" refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases). The formal definition of a database schema is a set of formulas (sentences) called integrity constraints imposed on a database.
Dremel is a distributed system developed at Google for interactively querying large datasets.. Dremel is the query engine used in Google's BigQuery service. [1]Dremel is the inspiration for Apache Drill, [2] Apache Impala, [3] and Dremio, [4] an Apache licensed platform that includes a distributed SQL execution engine.
The snowflake schema is represented by centralized fact tables which are connected to multiple dimensions. "Snowflaking" is a method of normalizing the dimension tables in a star schema. When it is completely normalized along all the dimension tables, the resultant structure resembles a snowflake with the fact table in the middle. The principle ...
By creating an abstract dimension, these flags and indicators are removed from the fact table while placing them into a useful dimensional framework. [6] A junk dimension is a dimension table consisting of attributes that do not belong in the fact table or in any of the existing dimension tables.