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ETL Azure Data Lake Storage data with Trifacta

CATEGORY: Big Data & NoSQL      STATUS: Available

 

Azure Data Lake Storage is a secure cloud platform that provides scalable, cost-effective storage for big data analytics.

ETL data from business-critical applications such as Salesforce, HubSpot, ServiceNow, Zuora, etc. into Azure Data Lake Storage in seconds. With Trifacta's Azure Data Lake Storage data connector, you can transform, analyze, and automate your Azure Data Lake Storage data pipeline in real-time. No code required.

 

Join Azure Data Lake Storage data with any data source

Combine datasets from any data source with your Azure Data Lake Storage data. Connect to any data - Trifacta's data integration workflow supports a wide variety of cloud data lakes, data warehouses, applications, open APIs, file systems, and allows for flexible execution, including SQL, dbt, Spark, and Python. Whether it's joining Azure Data Lake Storage data with your Salesforce CRM data, an Excel or CSV file, or a JSON file, Trifacta's visual workflow lets you interactively access, preview, and standardize joined data with ease.

Azure Data Lake Storage Screenshot
 

Azure Data Lake Storage to your data warehouse in minutes

ETL your Azure Data Lake Storage data to the destination of your choice.

 

No-code automation for your Azure Data Lake Storage data pipeline

Trifacta empowers everyone to easily build data engineering pipelines at scale. With a few simple clicks, automate your Azure Data Lake Storage data pipeline. No more tedious manual uploads, resource-intensive transformations, and waiting for scheduled tasks. Deploy and manage your self-service Azure Data Lake Storage data pipeline in minutes not months.

Ensure quality data every time.

No matter how you need to combine and transform data stored in Azure Data Lake Storage, ensure that the end result is high-quality data, every time. Trifacta automatically surfaces outliers, missing data, and errors and its predictive transformation approach allows you to make the best possible transformations to your data.

Schedule, automate, repeat.

Automate your Azure Data Lake Storage data pipelines with job scheduling so that the right data is in your Azure Data Lake Storage database when you need it. When new data lands in your Azure Data Lake Storage database, let your scheduled data pipelines do the work of preparing it for you—no manual intervention required.

 

"Trifacta allows us to quickly view and understand new datasets, and its flexibility supports our data transformation needs. The GUI is nicely designed, so the learning curve is minimal. Our initial data preparation work is now completed in minutes, not hours or days."

 

Use cases for the Azure Data Lake Storage data connector

  • ETL Azure Data Lake Storage data to Amazon Redshift

  • ETL Azure Data Lake Storage data to Google BigQuery

  • ETL Azure Data Lake Storage data to Snowflake

  • ETL Azure Data Lake Storage data to Databricks

  • ETL Azure Data Lake Storage data to MySQL

  • ETL Azure Data Lake Storage data to Microsoft Azure

  • Join Azure Data Lake Storage data with Google Sheets data

  • Prepare Azure Data Lake Storage data for data visualization in Tableau

 
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