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Azure Data Factory Unpacked

Data is one of the critical elements of any enterprise because it informs day-to-day operations. Running an organization or working on specific projects is not possible without the necessary information. Systems also depend on the information you feed into them for them to function. This suggests that data is an essential part of the operations of any company.

Data is a critical part of any entity. Over time, companies collect and store a massive volume of data. Turning such details into meaningful use can be a challenge if you do not have the necessary resources. Azure Data Factory (ADF)  proves to be a tremendous resource for business operators, and here are more details about this resource.

What is Azure Data Factory (ADF)?

ADF is a service that allows you to convert data from relational, non-relational, and various storage systems into useful information with data-driven workflows. As a result, entrepreneurs can:

  • Map strategies.
  • Create value.
  • Attain specific objectives using the details they retrieve from the ADF.

Data scientists, business decision makers, and analysts can also use the information that the ADF avails to draw the insight they need so they can advise management accordingly.

ADF is a managed, cloud-based data integration service. That means that it can handle:

  • Complex hybrid extract-load-transform (ELT),
  • Extract-transform-load (ETL), and
  • Data integration projects using a drag and drop interface.

Alternatives to Azure Data Factory

Several tools can serve as alternatives for ADF including;

1. IBM InfoSphere DataStage

The IBM InfoSphere DataStage is an ETL platform. It integrates data from multiple enterprise systems. Also, it is available both in the cloud and on-premise.

2. Apache Sqoop

If you want to transfer bulk data, you can consider using Apache Sqoop because it facilitates such exchanges between Apache Hadoop and such structured datastores as relational databases.

3. Data Virtuality Platform

The ability to access data from various sources is part of the prerequisites for most businesses today, and you can achieve that through a Data Virtuality Platform. As an integration solution, the Data Virtuality Platform promotes instant access and modeling of data from various databases and API with analysis tools.

4. Denodo

There is a wide variety of enterprise, cloud, and Big Data sources out there and getting unified access to such sources is critical if your company has a considerable volume of data. Denodo promotes access to a wide range of unstructured, enterprise, cloud, and Big Data sources for business owners who want to leverage the details that their systems generate.

5. Pipes

Integration of data from over 150 APIs and databases into a data warehouse through Pipes is possible, and it does not take much time.

Azure Data Factory Pricing

Azure Data FactoryThe cost of Azure Data Factory services depends on:

  • Whether a pipeline is active or not,
  • The number of activities you run,
  • The number of compute hours necessary for SQL Server Integration Services (SSIS), and
  • The volume of data you move.

In some cases, the pricing of Azure Data Factory services does not include setup, upfront, or termination costs because the cost of this service depends on usage.

The Role of ADF in Data Management

ADF plays a significant role in the management of data including;

  • Supports such procedures as building, debugging, deployment, operationalization, and monitoring of big data pipelines. The implication, in this case, is that you can integrate and deploy your ETL/ELT workflows to such environments as Dev, Test, PROD, among others.
  • It simplifies the processing of large volumes of data.
  • Facilitates the publishing of output data to such data stores as Azure SQL Data Warehouse for business intelligence apps. This means that users can organize raw data meaningfully and that will enhance the decision-making process.
  • Allows users to create and schedule data-driven workflows that can ingest data from different sources. Processing and transforming data using such services as Azure Machine Learning, Azure HDInsight Hadoop, Azure Data Lake Analytics, and Spark is also possible through ADF.

Advantages of ADF Over On-Prem Data Pipes

1. Patching Is Not Necessary

Sometimes, making changes in computer systems is necessary if you want to enhance their performance, update the software, or fix a particular problem. Patching makes changes in computer systems when the need arises, and it is an essential exercise for those who use on-premise platforms.

ADF will withdraw the need for patching systems from your shoulders since your cloud services provider will assume this responsibility. For that reason, cases of security vulnerabilities become the least of your worries. In turn, you can focus your attention on revenue-generating activities.

2. It Reduces Operating Costs

The fact that the number of compute hours necessary for SQL Server Integration Services (SSIS), the activities you run, and the volume of data you move dictate the pricing of ADF services suggests that this resource will not blow your budget through the roof. In fact, the total cost you expect to pay for ADF services will depend on how long your pipeline remains active.

3. No Hardware Expenses

Entrepreneurs focusing on reducing their operating costs will most likely automate their business processes. One of the things you should consider when developing an automation strategy for your enterprise is cloud services. The reason is that you will not need to invest in on-premise hardware when you opt for cloud services. Vendors of these services provide all the necessary equipment off-site.

ADF is a cloud service that saves you the cost of investing in the hardware you need to support this resource. This means that you will save on space and labor as well.

Although ADF’s primary role is to work with Azure storage services, it can integrate with other Azure services. This promotes seamlessness in business operations. More and more business owners are opting for interdependent systems or platforms that support the integration of existing applications in their offices. They know that doing so will improve productivity and ADF fulfills this requirement too.

If your enterprise has been in operation for a while now, there is probably a lot of data that remains unutilized for one reason or another. However, the ability to leverage such information can be the next big thing that will open new frontiers for your firm. ADF captures the details you need to understand your business better. As a result, you will gain the knowledge necessary for making decisions that will scale your operations.

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