Data is an invaluable business asset, and organizations can’t seem to get enough of it. The global business community consumes unimaginably large volumes of data every year — on the zettabyte scale. A recent report from Seagate and IDC forecasts data usage to grow by a 42.2 percent annual rate between 2020 and 2022. However, 44 percent of business data slips through the cracks, and as much as 68 percent of captured data goes unleveraged. Challenges in data management and security can lead businesses to hoard data at great expense without extracting any value from it.

Azure Data Factory or ADF is one of Microsoft’s answers to the data management problem. Let’s explore this solution and how you can leverage its features and capabilities to streamline your data management processes and policies.

What is Azure Data Factory?

Azure Data Factory is a cloud-based data integration, extract-load-transform (ELT), and extract-transform-load (ETL) service that allows the creation of data pipelines for orchestrating complex data flows and transformations at scale. ADF is fully managed by Microsoft and runs on Azure as a serverless service. It enables organizations to ingest, prepare, and transform data for various use cases such as on-prem to cloud migration, data engineering and analytics, data warehousing, and operational data integration.

How does Azure Data Factory work?

ADF essentially automates the workflows involved in drawing data from multiple sources, trimming and transforming that data into useful clusters or formats, combining the various datasets, and presenting the organized data to other platforms for storage or high-level analytics. It does this through the following processes and functions:

Connect and collect

Enterprises usually generate data from many different external and internal sources such as transactions, customer touchpoints, local file systems, and assets’ logs. The data may come in many different types; as structured, unstructured, or semi-structured; at different speeds and intervals; and through various channels.

Azure DF seamlessly integrates multiple data sources without needing custom-built data movement tools. It can automatically gather data from both on-prem and cloud sources to a centralized location such as Azure Data Lake Storage.

Transform and enrich

After the data reaches a central location, you can process or transform it using ADF mapping data flows. Transformation means modifying the data into logical or usable data sets to refine and enrich the data. It might involve merging multiple data streams, expanding complex data types into digestible strings, sorting and filtering data fields, and many other operations depending on the data in question.

ADF supports data transformation operations through various services, including Spark, HDInsight, Data Lake Analytics, and Azure ML.

CI/CD and publish

ADF supports continuous integration and delivery (CI/CD) that allows the movement of data pipelines from one environment to another using Azure DevOps and GitHub. Once the data has been transformed into consumable information, ADF automatically moves it to the chosen analytics platform for further processing, reporting, or visualization. The supported analytics and storage systems include Azure SQL Database, Azure Synapse Analytics, and Azure CosmosDB.

Monitoring

Azure DF has built-in tools for real-time pipeline monitoring running on PowerShell, API, Azure Monitor, and Azure Portal health panels. Monitoring services keep an eye on scheduled operations and report on progress, status, successes, and failures.

Pipeline executions

A pipeline is a logical group of activities representing a unit of work. An activity is a processing step in a pipeline. You can think of a pipeline as a set of executable instructions, rules, and procedures (functions) for performing a task. A pipeline run is an execution instance of a particular pipeline. An execution can be triggered automatically by a programmed event or manually passing arguments and variables to the run parameters. Triggers, executions, and runs are orchestrated in what’s known as control flow.

Linked services

These are strings that define ADF’s connections to external resources. A linked services string can represent a supported data store such as an SQL Server, Oracle database, Azure blob storage account, on-prem file system, or file share instance. It can also represent a computing resource housing or running a pipeline activity.

Why you need Azure Data Factory

Azure DF is an ideal data movement and integration solution for organizations relying on multiple data sources, particularly those running hybrid cloud systems. It enables seamless data movement, transformation, and integration between various cloud services and on-prem resources. ADF essentially reduces the time to insight by allowing multiple datasets to be packaged and analyzed together rather than running and merging analytical results from separate data streams. This way, you can gather and draw business intelligence insights from more sources without any of the precious data going to waste.

There are many ELT and ETL solutions out there. Let’s look at the key features and capabilities that set Azure Data Factory apart from other systems:

  • It supports SQL Server Integration Services (SSIS) packages, including custom SSIS components.
  • Users can easily design code-free data flows using the intuitive ADF Studio.
  • ADF rides on the secure and trusted Azure platform.
  • It gives a holistic view of data movement throughout the organization via native integrations with Azure Purview and other data governance services.
  • Azure Data Factory has a global presence; it’s currently available in over 40 regions.
  • ADF can handle large volumes of data with incredible speed and accuracy, even with high computation demands.
  • Activities and trigger automations reduce manual workloads and costs.

Leverage Azure Data Factory with Softlanding

Softlanding is a Microsoft Gold-Certified partner and managed services provider specializing in helping Canadian companies adopt, deploy, and implement Microsoft enterprise solutions. It takes some level of expertise and experience to integrate cutting-edge digital solutions with business workflows for maximum value and productivity. Let us do all the heavy lifting for a smooth transition to digital process through Azure Data Factory, Teams, Microsoft 365, or any other Microsoft solution. Contact Softlanding and start your digital transformation.

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softlanding

Softlanding is a long-established IT services provider of transformation, professional services and managed IT services that helps organizations boost innovation and drive business value. We are a multi-award-winning Microsoft Gold Partner with 13 Gold Competencies and we use our experience and expertise to be a trusted advisor to our clients. Headquartered in Vancouver, BC, we have staff and offices in Toronto, Montreal and Calgary to serve clients across Canada.

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