Azure Data Factory

Implement Azure Data Factory as part of your data integration solution to assist your organisation with automating data refreshes, transforming raw data into a structured format ready for data modelling, and cleansing data to ensure accuracy and consistency of your information.

How we can help you using Azure Data Factory

AGER BI can implement Azure Data Factory as part of your data integration solution which will assist your organisation with automating data refreshes, transforming raw data into a structured format ready for data modelling, and cleansing data to ensure accuracy and consistency of your information.

What is Azure Data Factory?

Microsoft Azure Data Factory (ADF) is a fully managed, cloud-based data integration service provided by Microsoft Azure. It enables organisations to efficiently move, transform, and manage data from a variety of sources, all within a single, unified platform.

Whether it is working with on-premises data, cloud data, or hybrid environments, Azure Data Factory helps streamline and automate data workflows, supporting a wide range of data integration, transformation, and orchestration tasks.

How Does Azure Data Factory Work

Azure Data Factory operates around the concept of pipelines which are essentially a series of interconnected data transformation and movement tasks. These pipelines orchestrate the flow of data between various data sources, perform necessary transformations, and load the data into a destination of your choice.

Key components of an ADF pipeline:

Datasets: Represent the data structures that ADF works with such as tables, files, or objects, and define the location and schema of your data.
Linked Services: Define the connection information for various data sources and compute resources (e.g. databases, storage accounts, or services).
Activities: Perform the tasks in a pipeline, such as copying data, transforming data, or executing a stored procedure or custom script.
Triggers: Automate pipeline execution by defining schedules or events that trigger pipeline runs, such as time-based schedules, file arrival, or system events.

Key Features

Data Movement	Azure Data Factory simplifies the process of ingesting and moving data across different sources and destinations, regardless of where they reside. It supports a broad set of connectors for both cloud and on-premises data sources, including SQL Server, Oracle, Amazon S3, Azure Blob Storage, and more.
Security and Compliance	Azure Data Factory is built with security in mind. It provides encryption in transit and at rest, secure access management via Azure Active Directory (AAD), and supports compliance with industry standards such as GDPR, HIPAA, and more.
Support for Advanced Analytics	By integrating with Azure services like Azure Machine Learning and Azure Databricks, Azure Data Factory can support advanced analytics workflows. This allows users to run machine learning models, perform real-time analytics, and trigger automated actions based on data insights.
Data Transformation	ADF offers powerful data transformation capabilities, enabling users to shape and modify data as it moves from one system to another. With its built-in transformation activities, users can apply business logic, clean data, aggregate information, and perform complex calculations without writing complex code.
Pipeline Orchestration	One of the standout features of ADF is its ability to orchestrate and automate end-to-end workflows. By creating “pipelines” users can define and schedule tasks that move and transform data in a coordinated sequence. This ensures data processes are consistent, reliable, and optimised.
Hybrid Data Integration	Azure Data Factory is not limited to cloud environments. It also allows integration with on-premises systems through a variety of connectors and the Azure Data Factory Integration Runtime (IR). This makes it ideal for hybrid cloud architectures, where data needs to move seamlessly between on-premises databases and cloud storage.
Monitoring and Management	ADF provides extensive monitoring and troubleshooting capabilities. The service includes a built-in monitoring dashboard where users can track the progress of data pipelines, view historical data movement logs, and receive alerts when errors or issues occur. This ensures visibility and control over the data integration lifecycle.
Scalability and Flexibility	As a cloud-based service, Azure Data Factory is highly scalable. It can handle everything from small datasets to massive, enterprise-level data operations. ADF automatically scales compute resources based on workload needs, ensuring optimal performance while keeping costs manageable.
Data Flow Management	ADF’s data flow feature enables users to design data transformation workflows with a graphical user interface (GUI), rather than having to write custom code. You can visually design, debug, and deploy data transformations, which makes it accessible for both technical and non-technical users.

Benefits

Azure Data Factory offers several key benefits for organisations looking to streamline and modernise data integration processes.

As a fully managed cloud service, it allows users to easily build, schedule, and orchestrate data workflows, enabling seamless data movement across various sources and destinations.

ADF supports a wide range of data connectors, making it highly versatile in connecting to both on-premises and cloud-based data stores. With its serverless architecture, users can scale resources up or down based on demand, ensuring cost efficiency.

ADF also provides advanced data transformation capabilities through integration with services like Azure Databricks and HDInsight, helping organisations process large volumes of data with minimal management overhead.

Additionally, the platform’s monitoring, logging, and alerting features ensure that data pipelines run smoothly, while its integration with Azure’s security and governance tools ensures compliance and data protection.

Seamless Data Integration

Cost-effective

Data Transformation

Hybrid Data Movement

Data Governance

Scalable and Managed Service

Orchestration and Scheduling

Monitor and Troubleshoot

Use

Azure Data Factory is suitable for use in a wide range of situations, including:

ETL Workflows

Extract data from various sources, apply transformations and load into data warehouses or other destinations.

Data Warehouse

Integrate disparate data sources into a centralised data lake or data warehouse to analyse and gain insights from data.

Live Data Stream

Ingest and process real-time data streams, enabling real-time analytics and decision-making.

Hybrid Data Migration

Migrating data from on-premises systems to the cloud without disrupting existing workflows.

Data Sync

Keep data in sync across various systems, ensuring updates in one data store are reflected in others.

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Free consultation

Schedule a free, no obligation consultation with our certified solutions experts to understand how AGER BI can assist with your data needs.

Deep dive and strategy

If you choose to work with us, we’ll design a strategy outlining how we can tackle your biggest pain points immediately, with a plan of action to transform you into a successful state-of-the-art data-driven business.

World-class business intelligence solution

We will implement the strategy phase by phase to deliver you a truly world-class cloud-based business intelligence solution that will transform your business.

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