Enterprise Data Lakehouse with Microsoft Fabric

Technologies: Microsoft Fabric, Dataflow Gen 2, Notebooks, Data Pipeline, Data Warehouse, Lakehouse

Extracted data from multiple sources using Copy Data activity and Dataflow Gen 2. Designed and implemented robust ETL pipelines in Microsoft Fabric to ingest, clean, and transform data into a Lakehouse and Warehouse. Performed incremental loading to ensure efficiency and accuracy. Built semantic models and developed interactive reports to provide real-time business insights, supporting data-driven decision-making.

Business Intelligence Dashboard for Sales Analytics

Technologies: Data Modelling, Power BI, SQL Server, Data Warehouse

Developed interactive Power BI dashboards and apps to track sales KPIs, identify trends, and forecast revenue, enabling stakeholders to make data-driven decisions.

Azure Synapse Pipeline for Real-Time Data Processing

Technologies: Azure Synapse, SQL, Data Lake, Data Warehouse

Built and deployed Azure Synapse pipelines to process streaming data and load it into a data warehouse, optimizing ETL workflows and improving processing efficiency.

Financial Data ETL Automation with SSIS

Technologies: SSIS, SSAS, SQL Server, Excel, Data Warehouse

Designed and automated the extraction, transformation, and loading (ETL) of financial data from multiple sources into staging and a data warehouse, ensuring data accuracy and significantly reducing manual effort. Implemented an SSAS Cube to create a multidimensional data model, enabling advanced analytical capabilities. Connected the SSAS Cube to Excel for streamlined data retrieval and reporting, providing users with intuitive and efficient access to insights.

Flask-Based Inventory Management System

Technologies: Python, Flask, REST APIs, Jenkins

Developed a web application for inventory management, featuring functionalities such as stock tracking, order management, and reporting. Designed and implemented REST APIs to enable seamless integration with other applications. Leveraged a Jenkins pipeline to automate the deployment of the application and APIs to a Kubernetes cluster, ensuring scalability and reliability for multi-user access.

REST API for E-Commerce Platform

Technologies: Java, Spring Boot, REST APIs, Postman

Designed and implemented a scalable REST API for an e-commerce platform to manage core functionalities, including user authentication, product management, and order processing. Utilized Postman for comprehensive API testing and validation. Created detailed API documentation to ensure seamless integration for developers and stakeholders.

Machine Learning Model for Payment Prediction

Technologies: Python, Scikit-learn, Pandas, Jupyter Notebook

Created a classification model to predict customers' next payment dates using historical transaction data, improving cash flow management.

Part 1: Getting Started with Querying with GraphQL in Microsoft Fabric

GraphQL, a powerful query language for APIs, allows developers to query multiple data sources using a single API and retrieve exactly the data they need. This article will walkthrough setting up a GraphQL API in Microsoft Fabric, with a focus on the essentials of querying data and managing relationships effectively.

CI/CD: Streamlining Deployments with GitHub Actions

Having worked in the field of business intelligence, my primary focus is on transforming data into actionable insights. However, in today's fast-paced tech landscape, understanding the broader ecosystem, including deployment processes, is crucial.

This is where Continuous Integration and Continuous Deployment (CI/CD) come into play.

Even though my day-to-day work revolves around business intelligence, I believe it's essential to grasp the fundamentals of CI/CD to ensure that the applications and solutions we develop are delivered efficiently and reliably.

Power BI DAX: Advanced Insights with CROSSJOIN Function

Power BI is all about making data work for you. In this article, we will explore an essential function 'CROSSJOIN' to unlock the full potential of your data. This function is a pathway to extracting valuable insights and facilitating data-driven decisions. Let's jump right in and explore.

Explore Bar Charts in Apache Superset

A bar chart is a graphical representation of data. Bar charts can be helpful for comparing and displaying data, especially when the data is categorized. They are frequently used in the business, economics, and social sciences to display data. Apache Superset is a modern, enterprise-ready business intelligence web application.

Data preprocessing for Associate Rule Mining

This highlights the importance of transforming raw data into a clean, structured format to improve the effectiveness of market basket analysis. Using a practical example, it demonstrates the process of preparing data for association rule mining, which uncovers valuable patterns and co-occurrences in transactional data.

Basic Overview on Data Mining

Data Mining also known as Knowledge Discovery of Data (KDD) is all about discovering hidden information and knowledge which we consider useful , from the massive collection of data. It is a process of discovering trends and patterns in large datasets to showcase relevant insights of it. Data mining origins are based on Classical statistics, Artificial intelligence, and Machine learning.