Getting your data from BigQuery to CARTO can be a pain. Managing pipelines for all your data sources just isn’t sustainable, but your reporting can’t be put on hold while you wait for IT or Engineering to get to your ticket.
With Panoply, you can eliminate that hassle—and all that wasted time. Set up code-free connections to both BigQuery and CARTO with just a few clicks. Then Panoply will automatically sync your data so it’s ready to analyze when you are.
It’s that simple: Unblock your data with Panoply.
BigQuery allows companies to perform analytics on very large read-only data sets stored within the Google Cloud. Being able to seamlessly access BigQuery data will empower Panoply customers to take this data, combine it with other data sources, and be able to query all the data in one place, which is crucial for data mining. BigQuery’s integration with Panoply lets you not only ingest any data source into one automated cloud data warehouse, but you can also analyze it with any visualization tool you need to get lightning fast insights.
Learn more:
Documentation
BigQuery Data Warehousing
BigQuery Business Intelligence
CARTO collects and analyzes location data to solve spatial problems and provide business outcomes. It uploads your spatial data, enriches it, and performs geospatial analysis. This BI tool provides geodata analytics, workflow integration, and million-point visualizations. Data scientists can use CARTO to simplify location data prep and collection. It interacts with your preexisting libraries and functions, or you can use its out-of-the-box spatial analysis models. CARTO’s development tools include its own visualization libraries, app development, scalability, data APIs, geocoding, and more. CARTO can run even faster and more powerfully with the Panoply integration. The automated Panoply pipeline continuously streams the entire ETL flow from input to processing to output and storage. Panoply offers the security, power, and speed of the only fully integrated cloud service that combines an automated ETL with a data warehouse.
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