Loaders are a set of business rules that identify how the raw data from a data source is to be used. Loaders take the data from the staging area, prepare it for loading into the Adaptive Suite, and then load the information. There are three types of loaders:
Discovery Metric Loader
Loads data from staging tables into Adaptive Discovery and maps columns in staging tables to dimensions and metrics in Discovery. It prepares the data by doing the following:
mapping the data in the staging area to assign a timestamp to the columns you specify for referencing the information
You can set the granularity of the timestamp. The timestamp lets you view data across different time periods.
converting the information into metrics and dimensions
A metric In Adaptive Discovery, a metric is similar to an account, but can be made up of any sort of data, not just financial data. Metrics can be displayed on dials just as accounts would be. is basically any collection or series of numeric data. Examples of metrics include monthly sales data, personnel expenses, and product defect count. Metrics can be aggregated. Dimensions are attributes of a metric. Dimensions cannot be aggregated. Dimensions provide a mechanism to group metrics. For example, you might have a dimension called Region whose values are North, South, East, and West. Each metric can have one of these values for the Region dimension, and this lets you group metrics (and the associated record) by what region they’re associated with.
applying SQL calculations and filters
You can use SQL to create calculations and filter conditions.
See Creating Metric Loaders for more information.
Loads data from staging tables into sheets and transactions in Adaptive Planning or Consolidation. It contains tabs for configuring:
Data Source Settings: Configures source and destination for the loader and the period settings for the loader.
Profiles: Create and manage profiles for column mapping and data mapping.
Column Mapping: Map Planning columns to a source column in a source system.
Data Mapping: Map data from Column Mapping to the Accounts, Levels and Dimensions data in Planning.
Business Rules: Skip selected account codes, change signs, and write SQL filters to further distil the data being loaded.