I am passionate about business analytics, driven by the realisation that vast amounts of data within organisations often remain underutilised, limiting their potential for impactful decision-making. As data technologies and analytics capabilities evolved, I recognized an opportunity to transcend traditional reporting and focus on strategic questions that facilitate growth and innovation. Today, I specialise in transforming raw data into actionable insights, enabling businesses to make informed, data-driven decisions. My motivation lies in empowering organisations to leverage their data fully, creating clarity and competitive advantages. By applying advanced analytical techniques, I aim to turn complex data challenges into avenues for success.
Together, let's transform your data into a strategic asset.
Throughout my career, I’ve consistently leveraged an analytical mindset to drive operational efficiency and business success. I began honing my skills in the logistics industry, where I developed and monitored key performance indicators (KPIs) using tools like Excel to optimise delivery times and reduce fuel consumption. Over time, my analytical expertise has evolved, expanding into data analytics and data science through continuous learning and practical application across diverse business domains. This journey has enabled me to apply predictive analysis, data visualisation, and process optimisation to solve complex problems, enhance decision-making, and deliver measurable improvements.
Demand Planning - Random Forest Regression
Our approach is focused on understanding your needs and providing practical solutions. From personalized consultations to hands-on assistance.
One of the largest retail chains in the world wants to use its vast data source to build an efficient forecasting model to predict the sales for each SKU in its portfolio at its 76 different stores using historical sales data for the past 3 years on a week-on-week basis. Sales and promotional information is also available each week, both product and store-wise.
However, no other information regarding stores and products is available. Can we still accurately forecast the sales values for every such product/SKU-store combination for the next 12 weeks?
Technologies : Python, Jupyter Lab, Scikit-Learn
Before anything else, preparation is the key to success :
Alexander Graham Bell, the inventor of the telephone.
Clean data is the foundation of accuracy and reliability when it comes to gleaning insights from analysis, leading to better decision-making by eliminating errors, inconsistencies, and biases. For this project, I want to demonstrate an understanding of the processes and technologies required to take raw data and transform it into clean, usable data.
Technologies Used: Python: Jupyter lab
In May 2024, more than 65,000 developers participated in Stack Overflow's annual survey, which explored various topics, including coding practices, the technologies and tools developers use, their aspirations for learning, AI, and their overall work experience.This project highlights techniques for extracting insights from data that is not consistently organized across column headers. By employing a range of analytical methods, the data has been leveraged to draw inferences that can help recruiters better understand the current and future landscape of skill supply and demand
Technologies Used: Python: Jupyter lab , Tableau
“If there’s one takeaway it’s that it’s okay to do small wins. Small wins are good, they will compound. If you’re doing it right the end result will be massive.”
Kevin Li - Co founder of Farmstead , formerly head of Yahoo growth
This project is designed to extract critical business insights from Walmart sales data. We utilise Python for data processing and analysis, SQL for advanced querying, and structured problem-solving techniques to solve key business questions. We also created pipelines to move the data between python and Postgres.
Technologies used: Python: Jupyter Lab, SQL: Postgresql
Road freight is not universally renowned for its investment and move towards cutting edge technologies. Whilst some firms are beginning to understand and invest in areas such as predictive analytics, AI, and machine learning. Many are still over invested in time- consuming, labour-intensive practices that measure historic trends and week old KPI’s.
We pride ourselves on our adaptability and commitment to excellence in every aspect of our service. Explore what we have to offer and how we can contribute to your success.
Feel free to reach out to us for any inquiries or to schedule a consultation. We are here to help with your data analysis, business intelligence, and data visualization needs.
Lee Wilson
Hull, United Kingdom
