Turning your data into insights.
I'm Jacques, a data analyst with a background in computer science analytics. I'm passionate about translating data into meaningful insights, and love building automated business intelligence tools.With over 7 years of experience in data analytics across multiple countries and diverse industries, I help companies create dashboards that support cross-team decision-making and perform ad-hoc analyses to guide business strategy.🇬🇧 🇫🇷
Booking analysis and visualisation for the UK National Rail, focusing on purchase trends, railcard usage and refunds patterns.
Subscriber behaviour analysis and visualisation for a video streaming platform, focusing on subscription trends, engagement patterns, and retention metrics.
Reviews analysis to uncover patterns in satisfaction, motivations and frustrations, with a focus on subjectivity to helps separate between factual and opinion-driven sentiment.
The public dataset includes booking records for National Rail in the UK from December 2023 to April 2024. Each record represents a customer’s ticket purchase, containing details such as the purchase date, travel date, price, origin, destination, and refund status.
Dashboard: MavenFlix Booking Analysis Dashboard
Ad-hoc Analysis: Early Bookings Analysis.pdf
GitHub : Booking Analysis Dashboard on Power BITechnology Stack: Power BI, PostgreSQL, Python, VS Code, GithubData: UK National Rail
The public dataset contains subscription records for MavenFlix, a fictitious video streaming platform, from September 2022 through September 2023. Each record represents an individual user' subscription, including the subscription cost, created/canceled date, interval, and payment status.
Dashboard: MavenFlix Subscription Analysis Dashboard
GitHub: Subscription Analysis Analysis Dashboard on Looker StudioTechnology Stack: Looker Studio, PostgreSQL, Python, VS Code, GithubData: Streaming Video Subscription
The public dataset contains records from the popular travel booking website, Booking.com, from July 2018 to July 2021. This dataset provides valuable insights into the experiences and opinions of customers who have stayed at various hotels across different locations.
Dashboard Video: Customer Sentiment Analysis Dashboard
GitHub: Customer Sentiment Analysis Analysis Dashboard on MetabaseTechnology Stack: Metabase, PostgreSQL, Python, Docker, VS Code, GithubData: Booking.com Reviews