For a modern business, data is immensely valuable, it is comparable to money. And it is growing exponentially- the daily amount of data generated is estimated to reach a staggering 463 exabytes, by 2025! Managing the data deluge effectively and leveraging the data to get real actionable business insights is at the top of every CDO’s mind right now.
For converting this raw data from various sources into actionable business intelligence, data engineering comes into play. Dealing with the creation, construction, and upkeep of the infrastructure that manages massive volumes of data efficiently, data engineering acts as the cornerstone for resilient business intelligence systems.
The meteoric rise of cloud data platforms has reshaped data engineering with its scalability, cost-effectiveness, and enhanced processing systems. It offers a resilient solution to the constraints faced by on-premises infrastructure in scaling.
Data engineering is evolving rapidly with the marriage of cloud computing and new-age data analytics platforms such as Microsoft Fabric. Microsoft Fabric ups the game by bringing in artificial intelligence, machine learning, Shortcuts, Data Mirroring and also generative AI (Copilot) to the table. Let us find out how Microsoft Fabric streamlines data engineering and helps unlock the full potential of data.
How Microsoft Fabric streamlines the data engineering journey
Data engineers manage several critical tasks in the process of data engineering. Being a comprehensive data-engineering solution, Microsoft Fabric joins data across all sources, produces batch or real-time analytics, and boosts enterprises with tailored and in-built tools that minimize complexity and yield actionable insights. The tasks include data ingestion, data integration, data processing, ensuring data quality and governance, and data pipeline orchestration.
Components from Power BI, Synapse Data Engineering, and Synapse Data Warehousing are well unified into a single environment. The Shortcuts, Data Mirroring, and Copilot features in Microsoft Data Fabric form a cohesive environment that simplifies and optimizes data ingestion, integration, processing, quality, governance, and data pipeline orchestration. Let us explore each of the features and understand the impact of streamlining.
Shortcuts in Microsoft Fabric- Transforming data engineering
Shortcuts are objects in Microsoft OneLake that point towards other storage locations. The locations can be internal or external to OneLake, or OneLake itself. They simplify the workflows, expedite data engineering tasks and streamline repetitive processes by automating actions. As a result, data engineers can build, deploy and manage the data pipelines without extensive coding.
Data Ingestion using Shortcuts in Fabric
Earlier data engineers would have to ingest data from various sources such as on-premises, Azure, AWS into a unified data lake. Microsoft Data Fabric makes the process streamlined, as data engineers can create shortcuts that point to existing data sources. The process eliminates latency associated with data copies and staging environments.
Data transformation
Data engineers spend considerable time and effort transforming the raw data into usable formats. Microsoft Fabric simplifies the process, as data engineers can just create shortcuts within lakehouses (tables or file folders), and these shortcuts synchronize metadata into usable formats (Delta/Parquet). The transformation allows seamless access to Spark, SQL, and relevant analytical engines. With this feature, Microsoft Fabric facilitates efficient data processing without manual intervention.
Data Integration
With Microsoft Fabric, integrating data is much simpler. Using shortcuts, data engineers can create a single virtual data lake by connecting to existing data sources. They can also handle permissions and credentials centrally, reducing complexity.
Data Warehousing
For large-scale data processing for an enterprise data warehouse, data engineers can create shortcuts to applicable data tables or files. This process averts unnecessary data duplication and thus, optimizes batch processing by directly accessing data via shortcuts. The benefits of this approach are minimized latency, efficient data movement, and simplified orchestration.
Real-time Analytics
If there is the need for real-time analytics, data engineers can create shortcuts in Microsoft Fabric that connect streaming data sources and allow seamless integration with real-time analytics engines. The results are faster and accurate real-time insights, reduced complexity, and streamlined data access.
Implementing Machine Learning models
Whether you need to build predictive analytics models or run ML experiments, the process is simple with Microsoft Data Fabric. By leveraging shortcuts in Fabric to relevant feature datasets, data engineers can skip data duplication during model training and seamlessly integrate with Azure ML or other ML tools. This speeds up model development and leads to better resource utilization while simplifying data access.
Data Mirroring- The standout feature of Microsoft Fabric
As we saw, there has been an exponential growth of data, and it is bound to rise. Managing and ingesting massive volumes of data across various apps, databases, and warehouses has become a strenuous task. Microsoft Fabric’s data mirroring capability enables seamless access to any database or warehouse within Fabric’s ecosystem. There is no need to switch clients or deal with proprietary storage formats.
As a result, it guarantees real-time replication of data as it captures all the transactions and transforms them into Delta tables in OneLake. The process eliminates the need for complicated ETL processes (extraction, transformation, and loading).
The mirrored database has an SQL Analytics Endpoint that houses metadata and points to OneLake data- making querying easy for SQL and citizen developers.
From bridging data silos, simplifying the data journey, and speeding up insights, Microsoft Fabric’s data mirroring feature reshapes data engineering. Its biggest game-changing offerings are its unified data access, real-time data replication, and streamlined data warehousing.
Copilot – A key attribute of Microsoft Fabric
Copilot is another trailblazing generative AI feature of Microsoft Fabric that revolutionizes data engineering. It analyzes code patterns, context, and user inputs to produce intelligent suggestions and automates code generation for data engineering tasks. From reducing manual coding efforts, to improving code quality, Copilot in Fabric nurtures collaboration among team members. Machine learning capabilities further boost the productivity of creating and handling data pipelines within the Fabric environment.
How Copilot redefines Data Engineering scenarios
In complex data transformations
This Gen AI suggests effective algorithms with pre-built functions for complicated data transformations. Those algorithms improve development and also guarantee precision in tasks such as data cleaning or feature engineering. In this way, copilot helps in creating data pipelines such as Azure Data Factory.
Optimize data pipelines
Copilot can also analyze the pipeline configurations and suggest optimization recommendations. It can offer parallel processing techniques or resource allocation adjustments that enhance performance and scalability.
Mitigating errors
Copilot also gives real-time feedback and suggests corrective actions after spotting potential coding errors or inconsistencies. These actions reduce debugging time and also guarantee optimized data processing pipelines in production environments.
Generating code snippets
Copilot augments data engineering with its code-generating capabilities. It produces code snippets for operations such as data parsing or SQL queries. It also automates documentation generation needed for data flow descriptions and transformation processes. Thus copilot, assures project transparency, maintainability and saves time.
Collaborative development
Copilot fosters collaboration among data engineers as it suggests best practices, optimizes codes and also gives alternative solutions. It also helps new team members to understand codebases easily and simplifies data workflow management.
Streamline Data Engineering with Saxon’s Microsoft Fabric Consulting Services
Are you looking to move your data estate to Microsoft Data Fabric and leverage cloud-scale analytics? With Saxon AI’s strategic Data Fabric Consulting Services, you can get strategic guidance and tailored support that streamlines data engineering and helps you realize the full potential of data analytics. So, have a unified data foundation for your entire organization with OneLake, enjoy a seamless data flow keeping silo challenges at bay, and leverage rich augmented data analytics and visualization to power your business decisions with Microsoft Fabric.
