Datasets that come from disparate sources often carry their own schemas and semantics that make data blending and accurate reporting exceptionally difficult.
Lore IO Data Standardization simplifies the process of mapping complex source files into a common format while developing rich logic for important calculated metrics.
Easily handle different file types and variations in data formats, schemas, and attributes in files you receive from channel partners by quickly mapping columns and values using an intuitive interface.
Standardize datasets from independent data providers to offer website users with consistent faceted search experience. Product managers and website owners are empowered to define transformation logic on their own.
Quickly prep and aggregate product and sales data from subsidiaries, franchisees, and business units for consistent reporting and analytics across the entire enterprise.
Develop sophisticated business rules to reconcile revenue, gross margin, and other key metrics that involve complex calculations and transformations. Avoid maintaining taxonomy and semantic rules in spreadsheets.
Use an intuitive interface to define target views and their expected schemas. When new source files are detected, Lore IO automatically converts them based on the expected schema and exports them to your destination storage.
Configure data validations to flag instances when source files contain unexpected elements, lack expected elements, or have invalid data. Lore IO automatically scans new files and triggers email and in-app alerts when data fails validation.
Lore IO handles any file format, easily ingesting files of any type and consistently converting them to your expected outputs.
Whether you are on-boarding dozens or thousands of source files, Lore IO makes it easy to line source and targets side-by-side and quickly map columns and values.
Save and apply mapping templates to speed up the on-boarding of many source files that require similar mapping rules.
Lore IO enables you to go beyond simple column and value mappings, and standardize data sets using taxonomy, reshape, and semantic rules. Easily integrate multi-source data into a single view using sophisticated expressions that handle the nuanced semantics of your data.