What is Azure Data Factory?-Visualpath

 Azure Data Factory (ADF) is a cloud integration system, which lets in transferring facts among onpremises and cloud structures in addition to scheduling and orchestrating complicated facts flows. ADF is

extra of an Extract-and-Load and Transform-and-Load platform instead of a conventional ExtractTransform-and-Load (ETL) platform. To attain Extract-and-Load goals, you could use the subsequent

approaches:

ADF has integrated functions to configure notably easy statistics flows to switch statistics among report

structures and database structures placed each on-premises and at the cloud. ADF is able to connecting

to many special database structures, like SQL Server, Azure SQL Database, Oracle, MySQL, DB2, in

addition to report garage and Big Data structures just like the nearby report system, blob garage, Azure

Data Lake, and HDFS.

Alternatively, you can additionally use ADF to provoke SSIS packages. This may be reachable in case

you want to put in force greater state-of-the-art statistics motion and transformation tasks.

As for transformation tasks, ADF can provision one-of-a-kind Azure offerings at the fly and cause scripts

hosted with the aid of using one-of-a-kind databases and different facts processing systems, like Azure

Data Lake Analytics, Pig, Hive, Hadoop, and Azure Machine Learning API offerings.

Why Azure Data Factory?

While you may use SSIS to gain maximum of the statistics integration dreams for on-premises statistics,

shifting statistics to/from the cloud gives some challenges:

Job scheduling and orchestration. A SQL Server Agent offering that is the

maximum famous to cause facts integration duties isn't always to be had at the cloud. Although, there are

some different alternatives, like SQL Agent offerings on SQL VM, Azure scheduler, and Azure

Automation, for facts motion duties, activity scheduling capabilities protected in ADF appears to be best.

Furthermore, ADF lets in construct occasion primarily based totally facts flows and dependencies. For

example, facts flows may be configured to begin whilst documents are deposited right into a sure folder.

Security. ADF robotically encrypts facts in-transit among on-premises and cloud sources.

Scalability. ADF is designed to deal with massive facts volumes, way to its integrated parallelism

and time-reducing capabilities and assist you to circulate many gigabytes of facts into the cloud in a be

counted of some hours. Azure data factory training online

Continuous integration and delivery. ADF integration with GitHub lets in you to

develop, construct and robotically set up into Azure. Furthermore, the whole ADF configuration will be

downloaded as an Azure ARM template and used to set up ADF in different environments (Test, QA and

Production). For individuals who are professional with Power Shell, ADF lets in you to create and set up

all of its additives, the usage of Power Shell. Azure data factory training in Hyderabad

Minimal coding required. ADF configuration is primarily based totally on JSON

documents and a brand new interface coming with ADF v2 lets in developing additives from the Azure

Portal interactively, without a good deal coding (that is one motive why I love Microsoft

technologies!).

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