Description
Practical Use Case and User Story
Green Taxi Trip Dashboard: As a fleet manager, I need a dashboard that analyzes Green Taxi trip patterns, revenue, and performance. It should highlight trip frequencies, peak hours, and route efficiency to optimize fleet management and improve service quality.
Sales Person Analysis Dashboard: As a sales manager, I need a dashboard to track and analyze sales representatives’ performance metrics. It should include sales volume, customer interactions, and conversion rates to identify top performers and refine sales strategies.
Pakistan Super League Dashboard: As a sports analyst, I need a dashboard that provides comprehensive insights into Pakistan Super League (PSL) performance. It should include team and player stats, match outcomes, and trends for fans and stakeholders.
Pakistan Super League Predictor Dashboard: As a PSL fan or analyst, I need a dashboard that predicts match outcomes using historical data and advanced analytics. It should offer probability-based forecasts based on team and player stats and match conditions.
Survey Report Dashboard: As a decision-maker, I need a dashboard to analyze survey results, including respondent demographics, feedback trends, and sentiment. It should help explore key insights to inform strategic planning and decision-making.
Tech Stack Involved
Data Collection & Integration
- APIs: REST, GraphQL (to collect data from external sources)
- Data Connectors: AWS Glue, Talend, Stitch (for integrating multiple data sources)
- Data Streams: Apache Kafka, AWS Kinesis (for real-time data streams)
- ETL/ELT
- ETL Tools: Apache Airflow, dbt (data transformations in the cloud)
- Cloud ETL Services: AWS Glue, Azure Data Factory (for scalable ETL pipelines)
- Data Processing: AWS Lambda (for event-driven data processing)
Databases & Data Storage
- Relational Databases: PostgreSQL, MySQL (for structured data storage)
- Data Warehousing: Amazon Redshift, Snowflake (for centralized data storage and fast queries)
- NoSQL Databases: DynamoDB, MongoDB (for unstructured or semi-structured data)
- Cloud Storage: Amazon S3, Azure Blob Storage (for storing large datasets or flat files)
Data Analytics & Visualization
Business Intelligence (BI) Tools:
- Amazon QuickSight: Scalable cloud-native BI service
- Microsoft Power BI: Comprehensive analytics and interactive dashboards
- Tableau: Popular for creating highly visual dashboards
- Google Data Studio: Free and integrated with Google services for basic dashboards
- Data Querying: SQL, PostgreSQL (for querying data for dashboarding tools)
Data Preparation & Transformation
- Data Wrangling Tools: Pandas, PySpark (for handling complex data transformations before visualization)
- Data Cleansing: Trifacta, OpenRefine (for preparing clean datasets for dashboarding)
Cloud Infrastructure
- Cloud Compute: AWS EC2, Azure VMs (for hosting dashboards or running backend services)
- Containerization: Docker (for packaging and deploying dashboard applications)
- Serverless Options: AWS Lambda, Azure Functions (for lightweight, event-driven tasks)
Collaboration & Version Control
- Version Control: GitHub, GitLab (to track dashboard development)
- CI/CD: Jenkins, GitLab CI (to automate the deployment of dashboards)