![]() The second crucial leg of the EL-T enablement is the decentralization of the Transformation portion of the data pipelines. How can DBT help in decentralizing data transformation? Better refresh speeds improve the analytics speed and enhance the user’s trust in data. Near-real-time sync - With the help of the above features, these tools can replicate data in near-real-time.This functionality makes the pipelines lightweight, thus reducing the network costs while improving the refresh timings. Incremental data refresh - The tool automatically takes care of incremental refresh without needing embedded logic for Change Data Capture(CDC).This feature helps to free up the developer's time and makes the changes available to the end-user in minutes rather than weeks. The tool automatically detects the metadata changes and starts synching the new columns and the data to the target. For example, if the source introduces a new column or changes the column name or the data type, no developer involvement is needed to replicate these changes in the target. Automated metadata sync - The tools’ awareness about metadata helps it sync not only data but also the metadata. ![]() This intelligence thus saves considerable developer efforts while increasing the quality of the pipeline. These connectors understand the data objects to expect in the source along with the source's metadata and the data model.
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