Top five reasons to integrate Azure Data Factory with Azure Machine Learning
In the world of big data, enterprises are embracing advanced tools and services to orchestrate and operationalize businesses to provide actionable business insights. Azure Data Factory (ADF), in particular, is one of the preferable tools for data integration and transformation at scale. Besides using ADF alone, modern enterprises are combining it with Azure Machine Learning (ML) tool for predictive analysis.
ML is a powerful data science technique that falls under the umbrella of Artificial Intelligence (AI) to forecast future outcomes or behaviors. Moreover, Azure ML is an enterprise-grade service offered by Microsoft to enable users to build, deploy and evaluate a predictive model. Most organizations have started creating a predictive pipeline by using ADF and Azure ML together.
This blog post aims to reveal how Azure Data Factory and Azure Machine Learning can work together to streamline data operations, enable team collaboration and accelerate productivity.
Realize the power of integrating Azure Data Factory with Azure ML
By integrating Azure Data Factory with Azure Machine Learning, you can solve several big data-related issues. The solution derived by combining ADF and Azure ML will enable you to carry out the following functions.
1. Data ingestion and orchestration
The ongoing COVID-19 pandemic has pushed the boundaries of digital innovation for organizations and move to the cloud for enhanced flexibility and scalability. An end-to-end solution offering both ADF and Azure ML services can help you to create data-driven workflows in the cloud. ADF is a data integration service that allows you to ingest, orchestrate and monitor data at scale.
2. Build a modern big data platform
Utilizing ADF and Azure ML together, you can build a modern data platform competent to handle critical data challenges of your organization. To evolve from traditional data architecture towards a state-of-the-art Azure data platform, you must focus on enhancing your data capabilities in AI, cloud, etc. And this can be made possible by integrating ADF with Azure ML.
3. Drive advanced analytics
Azure Data Factory and AI-based solutions have the strength to deliver integrated data and provide rich business insights. You can enhance existing solutions and maximize your enterprise’s ROI by leveraging Azure ML analytics services. Also, ADF is not a pure-play ETL (Extract Transform Load) tool but it is a part of Microsoft’s pay-per-use analytics suite.
4. Create predictive data pipelines
Utilizing ADF and Azure ML tools together will enable you to create pipelines for predictive analysis. These two tools will help you to make predictions on the data in a batch. For instance, you can determine and analyze a customer’s behavior pattern. You can build, test and deploy a predictive analytics solution using ADF and Azure ML in these three simple steps.
- First: Creating a training experiment to train your data
- Second: Converting your trained data to a predictive experiment
- Third: Deploying your scoring experiment as a web service
5. Bring business intelligence
In the digital era, data is of prime significance for small to large organizations. Data means information and this information can be brought to the fingertips through the modern tool called Business Intelligence (BI).
Data = Information = Business Intelligence
Azure ML combined with Azure Data Factory can provide you with the ultimate visualization of your entire data. These two tools can help you to drive business productivity and provide several benefits such as:
- Deliver real-time data insights
- Streamline data management process
- Automate data movement
Get your data moving with ADF and Azure ML
The Azure Data Factory + Azure ML solution is ideal for enterprises looking for a solution to handle the entire ML Ops process using only a single tool. ADF and Azure ML can help you to bring in a rich digital experience and data automation across the organization. By leveraging these two tools, you can create bog data pipelines and bring unparalleled insights to your business.
For instance, consider that an OTT (over-the-top) media company wants to identify the subscribers who are likely to repeal their subscription in consecutive weeks. Now the question is how to determine various ways of retaining the subscribers that might churn? The answer is clear — by leveraging a single solution that uses both ADF and Azure ML. ADF will enable the media company to transform their raw data into intelligent actions and orchestrate all the processes. While the Azure ML service will fetch the combined data and figure out customer churn.
Let your data predict!
Data Science and Artificial Intelligence are state-of-the-art techniques that enable business users to leverage data into actionable predictions. To realize the power of both these techniques, most enterprises are combining Microsoft’s two advanced services — Azure Data Factory and Azure Machine Learning. If you want to integrate ADF with Azure ML and build a bridge between your data and action-oriented recommendations, get in touch with our experts.
Originally published at https://www.softwebsolutions.com on September 15, 2021.
