Sigma computing functions8/24/2023 ![]() ![]() Union: Another method of combining multiple tables where two or more data sources are stacked on top of each other based on the configuration and alignment of fields and field types, also resulting in a new data source as a separate table. Similar to the VLOOKUP, function in Excel, the Lookup function in Sigma keeps all of the values from the base table plus any matching values from another data source a game of data-go-fish The Function is looking at the local key, and asking a different table if it has any matches.Joins: Joins combine two sources at a time, using one or more join keys to align matching information, resulting in a new table.Lookup: A function added to a base table that uses a lookup key, or identical value in at least two different sources, to match values across sources into the base table.In this tutorial, we will discuss the required conditions, correct configuration and performance optimization best practices for three methods of data blending in Sigma Computing.īefore we dive in, let’s define each of these methods: The Lag function typically shifts values down, while the Lead function shifts values up. It requires no code or special training to explore. Sigma is a cloud-native analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. It references a column and returns its values in offset positions, shifting the output down by a fixed number of rows. Take another look: Sigma delivers true self-service ad hoc analytics no LookML or manual SQL required. Even if all of your business data is warehoused in a single location such as the Snowflake Data Cloud, in depth analytics will require the combination of information across several tables, views, and perhaps a few CSV files too! The Lag function accesses data in preceding rows in the same result set, without having to join the table to itself. ![]() For example, if you group a table of city. Most data analyses require some form of data blending, or combining information from multiple sources in a controlled process. Sigma defines the window by the grouping level, and calculates results only from the rows within the window.
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