CSDL Data Processing Language
Data filtering with precision.
Cut through the noise with precision filtering
One of the biggest challenges for companies analyzing social data is how to transform messy, unstructured, actionable data. DataSift's VEDO categorization engine allows organizations to understand social interactions at a deeper level by adding the relevant business context.
Filter without limits
Explore beyond simple keyword searches and filter across metadata targets such as author, location, language and demographics.
Filter with precision
Use advanced operators and logic such as regular expressions, contextual search, text pattern matching and substrings to get most relevant data.
Filter across multiple sources on the STREAM platform
Save time by applying a single filter across multiple data sources, for both historical and real-time data filtering.
Curated Stream Definition Language
DataSift’s CSDL allows customers to create interaction filters that sifts through social data in real time by specifying conditions on any of the attributes present in the raw data objects, including all their metadata. For PYLON products, interactions filters record data into indexes that are explored using analysis queries to retrieve aggregated results from the index. By defining their own rules and tags using CSDL, users can further enrich the selected data and add custom metadata to their application.
CSDL in action
To see how CSDL works in action, here is an example of a filter created for the automotive industry.
The return block returns a 5% sample of all stories, comments, likes and reshares which mention Ford, BMW or Honda, and have a Facebook topic in the Cars or Automotive category. The goal is to focus on these 3 brands when the topic of discussion is their vehicles, excluding mentions of the brands in other contexts such as event sponsorship and pop culture, maximizing signal.
The feature tags segments the data by whether the discussion is about automotive style or practicality. It's the quality of these thematic or attitudinal tags, when cross-referenced with demographic segments, that lead to consumer insights.
The brand tags allow you to easily segment your recording by brand when looking at top topics, links or hashtags. Learn the syntax using our CSDL explorer.