Collaborative Projects – Leveraging team work

Participating in the Data Analytics Bootcamp at Le Wagon I gained valuable insights into effective teamwork, learning how to collaborate, communicate and leverage each team member’s strengths to successfully develop and deliver data projects.

real state french market

Final project of Data Analytics Bootcamp, le Wagon, Batch1334. Team Work of 5. Score cities in France to invest. Develop a clustering and ranking system of French areas that combines the interest of two specific user profiles: leisure and investor

real state french market

Combining both tourism-related factors and investor-driven factors. Performance overview through sales, ROI, housing score, sales price m2, investment score and vacancy rate-

real state french market

Key takeaways & recommendations based on the scoring and clustering results for leisure & investor profiles.

house renting analysis

Team work project of 5. Case study AIRBNB.Optimize the listing offering for analyse to increase overall sales and customer satisfaction. KPI’s from room type, availabilty rate, average price, average review score and revenue. 

house renting analysis

Room type deep analysys. Review scores are lower for slower response rates, suggest to reach out to hosts and push them to respond within a day to increase renter satisfaction. Availability Rate by Room Type.

house renting analysis

Pricing for booked vs non booked listings over time. Revenue overtime analysis.

SoloGenius – Empowering Data Analytics

Projects developed independently during the Data Analytics Bootcamp at Le Wagon, demonstrates the power of my individual skills in the world of data analytics. I gained hands-on experience in data collection, analysis, visualization and presentation.

chart formating

data visualization by adjusting colors, fonts, labels and styles .

charting with export

Save and exporting charts from data visualization tools in various formats such as images, PDFs or spreadsheets.

chart count

Analysis to quantify and assessing the frequency of specific chart types.

stock analysis

Systematic evaluation of financial data, market trends, and company performance.

summary analysis

Digital marketing analysis by: turnover, CTR, ROAS, clicks, cost

main results analysis

KPIS: turnover, cost, ROAS, nb_sessions and transactions. Trend over time.

campaign, orders & sales 

Campaign analysys: channel, impressions, turnover. Order analysis: turnover, margin, % margin, customer segment. Sales analysis: categories, segment, margin and % margin.

campaign by channel

Analyzing the turnover of the SEA non-branded campaign involves assessing the revenue generated specifically from non-branded search engine advertising, providing insights into the effectiveness of these marketing efforts in driving sale.

campaign by time & channel

Analyse the turnover and cost of SEA non-branded campaign by Quarter, month and day


Analyse the qty and % margin by categorie , cattegory_2 and product name.


Analyse the turnover, qty and % margin over time. It cool be interesting to add a brekdown by category.


Add optional metrics as nb_session, impressions, KPI analysis: turnover, ROAS over time.

NPS global score

Analysis by transporter type and segment. Current month satisfaction, average overall score, customer satisfaction over month by domain.

NPS by transporter

Current month transporter NPS  NPS over month by transporter, delivery customer satisfaction over month by transporter,  delivery reviews over month by transporter.

nps:order by customer

Data analysis and reporting to sort Net Promoter Scores (NPS) by individual customers. It helps identify which customers have the highest and lowest NPS, allowing businesses to focus their efforts on improving relationships with promoters and addressing concerns of detractors.

global analysis by month

Customer analysis by global note over month, customer satisfaction over month by domain.

global score

Customer analysis, current month satisfaction, NPS over month,  customer satisfaction over month by domain.

score by segment

Customer score analysis by average NPS by segment, NPS over by segment,  satisfaction over month by domain.