Azure data factory services
Orchestrate your data & automate data transformation at scale with ADF
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.
With 90+ in-built connectors perform data integration at enterprise scale and requirement
UI driven graphical mapping to monitor data pipleline & flows code free
Data Factory has been certified by HIPAA and HITECH, ISO/IEC 27001 & ISO/IEC 27018
Pay-as-you-go and scale the platform as per your needs in the future
Use autonomous ETL & ingest all your data with integrators and connectors
Rehost SSIS servers, connect with Azure Synapse, and drive led Analytics
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:
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.
