You will get sentiment analysis using ML, Databricks and PowerBI
Project details
Title: Transforming Customer Feedback into Actionable Business Insights
This project focused on developing a scalable analytics framework for a network of 45+ café locations. By leveraging Databricks, Natural Language Processing (NLP), and Power BI, the solution transformed raw customer reviews and operational data into clear, actionable insights.
Using Apache Spark on Databricks, data was ingested and processed efficiently through a medallion architecture. An NLP pipeline built with Python (SpaCy, Word2Vec, LDA) extracted sentiments, key topics, and emerging trends from unstructured text. These insights were combined with operational metrics and visualized in Power BI dashboards to highlight satisfaction trends, performance hotspots, and service feedback across locations.
The end result was a fully automated data pipeline that enabled improved service quality, enhanced decision-making, and deep insight into customer behavior and preferences.
Tech Stack: Databricks, Apache Spark, Python (SpaCy, Gensim), Power BI, Azure Storage
This project focused on developing a scalable analytics framework for a network of 45+ café locations. By leveraging Databricks, Natural Language Processing (NLP), and Power BI, the solution transformed raw customer reviews and operational data into clear, actionable insights.
Using Apache Spark on Databricks, data was ingested and processed efficiently through a medallion architecture. An NLP pipeline built with Python (SpaCy, Word2Vec, LDA) extracted sentiments, key topics, and emerging trends from unstructured text. These insights were combined with operational metrics and visualized in Power BI dashboards to highlight satisfaction trends, performance hotspots, and service feedback across locations.
The end result was a fully automated data pipeline that enabled improved service quality, enhanced decision-making, and deep insight into customer behavior and preferences.
Tech Stack: Databricks, Apache Spark, Python (SpaCy, Gensim), Power BI, Azure Storage
Machine Learning Tools
Apache Spark, Apache Spark MLlib, Azure Machine Learning, Microsoft Excel, Microsoft Power BI, NumPy, pandas, Python, Python Scikit-Learn, SciPy, SQL, Tableau, Word2vecWhat's included
| Service Tiers |
Starter
$50
|
Standard
$150
|
Advanced
$300
|
|---|---|---|---|
| Delivery Time | 2 days | 4 days | 6 days |
Number of Revisions | 2 | 3 | 4 |
Number of Model Variations | 1 | 2 | 2 |
Number of Scenarios | 3 | 4 | 4 |
Number of Graphs/Charts | 5 | 5 | 9 |
Model Validation/Testing | |||
Model Documentation | - | - | |
Data Source Connectivity | - | ||
Source Code |
About Ehtisham
Data Engineer | Data Analyst | Databricks | Python | Sql | Azure
Lahore, Pakistan - 12:07 am local time
I am a Data Engineer & Data Analyst with 2+ years of experience in building scalable data pipelines, optimizing databases, and creating insightful dashboards. I help businesses leverage data for decision-making, automate workflows, and improve operational efficiency.
🔍 My Services:
âś… ETL & Data Pipelines: Automating data workflows using Apache Airflow, SSIS, Python, SQL, and Microsoft Fabric.
âś… Big Data & Cloud Solutions: Processing large datasets with Databricks, PySpark, Azure, AWS, and Google Cloud.
âś… Data Warehousing & Modeling: Designing optimized data warehouses, data lakes, and data marts for structured storage.
âś… Database Management: Query optimization and performance tuning for MySQL, PostgreSQL, Oracle, and MSSQL.
âś… Business Intelligence & Reporting: Creating interactive Power BI, Tableau, and Looker dashboards for better decision-making.
âś… API Integration & Automation: Extracting, transforming, and integrating data from REST APIs, SaaS platforms, and third-party sources.
âś… Data Cleaning & Preprocessing: Ensuring high-quality, accurate, and well-structured datasets for analysis.
đź› Tools & Technologies:
🔹 Programming: Python, SQL, DAX
🔹 Databases: MySQL, PostgreSQL, MSSQL, Oracle
🔹 Big Data & ETL: Apache Spark, Databricks, Apache Airflow, SSIS, Talend, Microsoft Fabric Data Factory
🔹 BI & Visualization: Power BI, Tableau, Looker, Google Data Studio
🔹 Cloud & Data Warehousing: Microsoft Fabric, Azure Synapse, AWS Redshift, Snowflake, Google BigQuery
🔹 API & Automation: REST APIs, FastAPI, Postman, Web Scraping
🔹 Version Control: Git, GitHub, Bitbucket
đź’ˇ Why Choose Me?
✔️ Efficient & Scalable Solutions: I design optimized, high-performance data workflows.
✔️ End-to-End Expertise: From data collection to visualization, I handle the full data lifecycle.
✔️ Data-Driven Problem Solving: I help businesses uncover patterns, trends, and insights for growth.
✔️ Timely Delivery & Clear Communication: I ensure fast turnaround times and well-documented processes.
📩 Let’s Discuss Your Data Needs!
Need a Data Engineer or Analyst to build a data pipeline, integrate APIs, optimize databases, or create BI dashboards? Let’s connect and make your data work for you! 🚀
Steps for completing your project
After purchasing the project, send requirements so Ehtisham can start the project.
Delivery time starts when Ehtisham receives requirements from you.
Ehtisham works on your project following the steps below.
Revisions may occur after the delivery date.
Meeting with client
To understand business requirements and scope of the project
Looping in client
Get into loop, give continous update and share progress with client.