Rajendra Ongole
Microsoft Data Platform MVP | Lead BI Engineer @Bosch Digital | Super User Fabric Community | MCT
BOSCH,BI-SPECIALIST/ARCHITECT
Hyderābād, India
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I am currently working as a BI Lead Specialist within the Engineering and Tech Lead Team at Bosch Digital. Holding more than 8 certifications from Microsoft, such as Microsoft Certified Fabric Analytics Engineer, Power BI Analyst, and Microsoft Certified Trainer. I’ve shared insights in Power Platforms forums through sessions, and I contribute through blogging. I worked on different projects, delivering insights to clients. My current skills include: Microsoft Fabric, Microsoft Power BI, SQL, Azure Databricks, Microsoft Excel, Python, and Spark My knowledge-sharing efforts extend across various platforms, including writing blogs, technical reviews of books, forum participation, and live sessions. I take pride in actively participating in and contributing to the Microsoft forums, where I consistently share valuable insights and knowledge.
Awards
Area of Expertise
Topics
Simplifying Data Ingestion into Microsoft Fabric Data Warehouse
Learn how to streamline your data loading processes into the Microsoft Fabric Data Warehouse with ease and efficiency. This guide explores best practices for integrating, transforming, and optimizing your data pipelines, enabling faster insights and better scalability for your analytics. Simplify your workflows and harness the full potential of Microsoft Fabric for seamless data management.
Setting Up Data Warehousing in Microsoft Fabric
Introduction.
What is the Microsoft Fabric Warehouse?
The difference between a data warehouse and a database.
Comparing the lakehouse and warehouse in terms of fabric.
Benefits of a Fabric Warehouse.
Creating a data warehouse in Fabric.
Ways to import data to a warehouse.
Creating tables and importing data using SQL scripts (DDL and DML).
Import tables using a data pipeline.
Import data using Dataflows Gen2.
Creating relationships between tables and the sales measure.
Building a matrix in Power BI.
Seamlessly Integrating On-Prem SQL Server with Microsoft Fabric Lakehouse
Connect and visualize your on-premises SQL data using Microsoft Fabric Lakehouse's. Discover the seamless process of establishing a secure connection to your data sources within your organization's network. Microsoft provides the On-Premises Data Gateway to securely bridge the gap between your on-premises environment and the cloud.
End-to-End Solution Design with Microsoft Fabric: Simplify, Scale, Succeed
Microsoft Fabric promises a comprehensive solution, offering an impressive range of analytics capabilities, including data engineering, integration, real-time analytics, and business intelligence, all in one package.
we go through the end-to-end Power BI project using various components of Microsoft Fabric. Join us to understand the full scope of Microsoft Fabric's functionalities in real-world applications.
Set up a new Lakehouse in Microsoft Fabric.
Upload tables from multiple sources using different ways to the Lakehouse.
Create a data model and calculations directly within the Lakehouse.
Build a Power BI report using DirectLake mode.
Data Activator in Microsoft Fabric
Understand Data Activator.
Understand triggers, conditions, and actions in Data Activator.
Get data from Power BI Reports and Event Streams with Data Activator.
Assign data and create triggers in Data Activator
Creating a Microsoft fabric end to end solution.
Microsoft Fabric promises a comprehensive solution, offering an impressive range of analytics capabilities, including data engineering, integration, real-time analytics, and business intelligence, all in one package.
It features key components like Power BI, Synapse, and Data Factory, catering to professionals across the data spectrum. The highlight is OneLake, a central architectural component of Microsoft Fabric, designed to foster collaboration among data professionals, paving the way for a new era of data-driven success.
In this session we will be building an end to end solution starting from ingesting data into a lakehouse and visualising the same in Power BI
Building Efficient Data Pipelines in Microsoft Fabric
Efficiently move data from diverse sources to your analytics environment with Microsoft Fabric. Automate and orchestrate data ingestion workflows with robust pipeline capabilities.
Transform raw data into valuable insights quickly and with minimal effort.
Building Data Warehouse, Lakehouse and SQL Endpoint in Microsoft FabriC
This presentation is focused on how to build data warehouse, ingest data from Microsoft SQL Server, create Lakehouse and use the SQL Endpoint object in Microsoft Fabric
Copilot for Power BI
Copilot for Microsoft Fabric Public Preview is available in Power BI. Copilot helps you use the transformational power of generative AI to get the most from your data.
Data Engineering in Microsoft Fabric
In this session we will do a deep dive into the data engineering workload in Microsoft Fabric. We will cover the end-to-end data engineering capabilities including the lake house, SQL Endpoint. Join the session to learn more about Data engineering.
Data warehouses in Microsoft Fabric
Describe data warehouses in Fabric
Understand a data warehouse vs a data Lakehouse
Create and manage datasets within a data warehouse.
Microsoft Fabric BI- Data Engineering Use case
Microsoft Fabric aims to revolutionize the access of data and AI services to consolidating all relevant components on to a unified platform. In this session we will delve into various data engineering services and construct a comprehensive lake house utilizing fabric components
Microsoft Fabric BI- Data Engineering Use case
Synapse Data Engineering
Build Lakehouse
Lake house Architecture
Lakehouse Explorer
SQL Endpoint of Lakehouse
One Lake
Workspace
Shortcuts
Built-in Modelling view
Generate Power BI Report
Field Parameters in Power BI
What is Fields Parameter?
What does it do?
How to use it in Power BI
How to call field parameters from what if parameters field
Dynamic parameter addition in report
Report preparation using Dynamic parameter
Dynamic selection of Category in Line chart using Power BI
Category fields in entity at a time how can we compare two fields dynamically Hassle free using DAX function, without any advanced functionalities used in Power BI.
Dax In Power BI
Introduction
Import data & create data model
Define relationships
Create new measure using sum function
Format measures
Edit & delete measures
Create new measure using count function
Create new measure using distinct function
Add comments to measures
Create new measure with operators
Quick Measure tool
Create calculated column
Measure vs. calculated column
Measure that references another measure
Iterator functions
Time & date functions
Find function
If function
Calculate function
Recap
Happy to Help if there is any questions
Data analysis in Power BI
Introduction
Import data & create data model
Define relationships
Create new measure using sum function
Format measures
Edit & delete measures
Create new measure using count function
Create new measure using distinct function
Add comments to measures
Create new measure with operators
Quick Measure tool
Create calculated column
Measure vs. calculated column
Measure that references another measure
Iterator functions
Time & date functions
Find function
If function
Calculate function
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