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    Data Factory
    Why Azure Data Factory?
    • Create data-driven workflows
    • Build Pipelines, activities, and Data sets
    • Bring Diverese data sources under one roof
    • Reduce time-to-insight

    Azure Data Factory enables organizations to connect & ingest data from multiple & rich variety data sources. You can Rehost SQL Server Integration Services (SSIS) in a few clicks, ingest all your on-premise and SaaS data, build ETL & ELT pipelines, and so much more easily. If you are looking for a powerful cloud data platform to orchestrate, monitor and manage your data pipeline then Azure Data Factory is for you.

    As Microsoft Gold Partners, Polestar Solutions is here to improve your operational productivity & help your visualize your data pipelines. We can help you migrate from SSIS to Data warehouse eliminating the need for multiple servers for data ingestion.

    Features of Azure Data Factory
    Enterprise Data Ready

    With 90+ in-built connectors perform data integration at enterprise scale

    Code-Free Transformation

    UI driven graphical mapping to monitor data pipleline & flows code free

    Secure Data Integration

    Data Factory has been certified by HIPAA and HITECH, ISO/IEC 27001 & ISO/IEC 27018

    Cost-Effective

    Pay-as-you-go and scale the platform as per your needs in the future

    Intelligent & Powerful

    Use autonomous ETL & ingest all your data with integrators and connectors

    Easy to use

    Rehost SSIS servers, connect with Azure Synapse, and drive led Analytics

    Modern Data Warehouse with Azure
    Data Warehouse with Azure
    Facilitate Seamless Data Integration with Azure Data Factory

    Accelerate your data transformation with ADF by organizing your raw data into data stores and data lakes to make better decisions. With data flows you can build complex ETL processes visually. Get Azure Data Factory services with Polestar Solutions as your partner of choice to get:

    Hybrid Data Integration

    Integrate data securely over a private network with Azure managing your virtual network with Apache Spark service taking care of code generation, Azure Integration Runtime to handle data movements, and build powerful data flows with Azure Synapse Analytics

    Modernize SSIS

    With Deployement wizard tools and fully customizable solutions Azure Data Factory is compatible with your third party components. It lets you focus on your data to provide a unified experience of handling your data with the latest innovative and intelligent solution in the cloud

    Graphical UI

    With a Graphical user Interface Azure Data Factory has drag and drop features that allows users to create Data integration pipelines with ease. This eliminates the need of learning or using proprietary knowledge in traditional ETL platforms, thus avoiding configuration issues

    Integrations of Azure Data Factory
    Integrations of Azure Data Factory
    FAQ

    Azure Data Factory is Azure's ETL Cloud service that offers a code-free Graphical User Interface (GUI) for serverless data integration and data transformation. It is used to prepare data, construct ETL and ELT processes, and orchestrate and monitor pipelines code-free.

    Azure Databricks, an Analytics platform opens a collaborative space for Data Engineers and Data Scientists, whereas, Azure Data Factory is primarily focused on Data integration and mapping data flows. Azure Data Factory known for its GUI to drag and drop data features in creating pipelines helps visualize data flows visually, whereas Databricks uses Python, Spark, R, Java, or SQL, therefore, requires a certain amount of coding knowledge.

    Though Azure and SSIS are both ETL tools, Azure Data Factory, in addition to its native data factory functionality, allows for the creation of an SSIS runtime to store and execute SSIS packages. SSIS though it comes pre-built with SQL servers, it cannot connect with services like Azure Databricks, Azure Synapse, etc. Whereas with ADF, you can connect with SSIS, Powerquery, and other services along with designing both ETL and ELT flows.

    The data-driven workflows in Azure Data Factory works in 4 steps which are: Collect, Transform, Publish, & Monitor. In the Collect phase, data is collected from multiple disparate sources into blobs or clusters. In the Transform phase, data is transformed and enriched with computing services like Hadoop, Data Lake Analytics, etc. In the Publish stage, the data in business-consumable format is loaded into the BI or Analytics tool. In the Monitor stage, pipeline monitoring activities and analytics deployment is done.

    Get Started On Your Data Journey with Azure Data Factory
    Begin Your Azure Cloud Migration Journey Now!
    Why Polestar Solutions for your Azure Data Factory needs?
    • 7+ Years of Professional Experience
    • Certified Microsoft Azure Experts
    • Faster Deployment
    • Top Cloud Solution Providers
    • 24*7 Customer Support
    • Established architectural planning
    • Low migration risk
    • Integrated microservices