Real Time - Analytics with Azure Databricks:

Real Time - Analytics with Azure Databricks:

This beginner-friendly article explores Azure Databricks in IIoT, detailing its role in enhancing data analytics from ingestion to data visualization, machine learning. It includes a practical case study on wind turbine optimization, showcasing how Azure Databricks addresses key challenges in modern data analytics

Akhil Gurrapu
PL-300: Microsoft Power BI Data Analyst Certification Roadmap

PL-300: Microsoft Power BI Data Analyst Certification Roadmap

Your go-to guide for conquering the PL-300 Power BI Data Analyst exam, packed with practical tips and resources for success.

Akhil Gurrapu
Data Integration in Microsoft Fabric Data Warehouse

Data Integration in Microsoft Fabric Data Warehouse

Uncover the power of Microsoft Fabric Data Warehouse. Learn its key features, ETL process, and data loading strategies. Explore data pipelines, advanced SQL capabilities, and Dataflow Gen2. Get hands-on with workspace setup, lakehouse creation, and data analysis. Master data integration with Microsoft Fabric.

Akhil Gurrapu
Data Warehouses in Microsoft Fabric

Data Warehouses in Microsoft Fabric

Explore the power of Microsoft Fabric's data warehouse, designed for seamless collaboration among data professionals. Learn data ingestion, storage, querying, modeling, and visualization essentials. Create your own Fabric data warehouse and harness insights for effective business intelligence.

Akhil Gurrapu
Understanding the Role of a Fabric Administrator

Understanding the Role of a Fabric Administrator

This article provides a concise overview of the Fabric Administrator's role in Microsoft's Fabric platform. It explains key concepts, administrative tools, and responsibilities associated with Fabric administration. The article also emphasizes security management and governance features crucial for data integrity and compliance.

Akhil Gurrapu
Apache Spark for data ingestion into Microsoft Fabric Lakehouse using Notebooks

Apache Spark for data ingestion into Microsoft Fabric Lakehouse using Notebooks

Explore the power of Apache Spark and Python for seamless data ingestion into Microsoft Fabric Lakehouse. Dive into Fabric notebooks, a scalable and systematic solution that empowers you to ingest external data, configure authentication for external sources, and optimize your data loading process.

Akhil Gurrapu
Microsoft Fabric Lakehouse and Medallion Architecture

Microsoft Fabric Lakehouse and Medallion Architecture

Explore how Fabric's Lakehouse solution, empowered by the flexible Medallion Architecture, transforms data handling and analytics for businesses. Learn about the architecture's layers, implementation, simplified data querying, reporting, and best practices for secure and efficient data management.

Akhil Gurrapu
Apache Spark in Microsoft Fabric:

Apache Spark in Microsoft Fabric:

In this article, discover the key features and advantages of using Apache Spark in Microsoft Fabric. Explore its versatile language support, Spark settings, and rich library ecosystem. Learn how Microsoft Fabric seamlessly integrates Spark for interactive analysis and automated data processing, making it a powerful tool for data professionals.

Akhil Gurrapu
Data Factory Pipelines in Microsoft Fabric

Data Factory Pipelines in Microsoft Fabric

EExplore the power of data pipelines in Microsoft Fabric. Learn how these pipelines streamline data transfer and transformation, using activities, parameters, and runs for efficient data management. Discover a code-minimal approach to handling data with flexibility and ease.

Akhil Gurrapu
DataFlows (Gen2) in Microsoft Fabric

DataFlows (Gen2) in Microsoft Fabric

Explore how Microsoft Fabric's Dataflows (Gen2) revolutionizes data engineering in the retail industry with global operations. This essential tool simplifies the extraction, transformation, and loading (ETL) processes, making it an invaluable asset for data engineers. Discover its key features, advantages, and limitations, and learn how to create workspaces, lakehouses, and dataflows for efficient data ingestion.

Akhil Gurrapu