Santiago Rojas Cisneros

Business Analytics student with experience in developing data solutions for business cases. Led projects involving data architecture design, dashboard creation, and financial analysis. Skilled in data management and predictive modeling, utilizing tools like R Markdown, Power Query, and Power BI to support strategic decision-making and optimize processes.

Business Analytics Platforms for Organizations | Draxton – Business Opportunity Analysis and Data Architecture Design (2024)
Level: Advanced
Last update: September, 2024.

Collaborated with Draxton to analyze a key business opportunity as the representative of my team at Tecnológico de Monterrey.
My team and I designed a scalable data architecture in Azure for Draxton, defining the technical specifications required for its implementation.
We presented a preliminary dashboard that provided actionable insights, automated processes, and optimized data analysis to identify critical areas.
Additionally, we developed a financial analysis to estimate the costs of the project, ensuring alignment with Draxton’s objectives.
Problem-solving skills and leadership were essential as I led the team to meet project deadlines and objectives.

Indicadores y Riesgos con Visión Estratégica | KPI Development and Dashboard Design (2024)
Level: Advanced
Last update: May, 2024.

Collaborated in the development of KPIs and performance indicators to assess strategic risks for an ongoing project.
Throughout the course, I transformed and managed data using R Markdown, Power Query Excel, and Power BI, ensuring data accuracy and alignment with strategic objectives.
Developed a presentation narrative to communicate progress and findings effectively to stakeholders, focusing on the evolution of key metrics and risk management strategies.
Presented final results through a series of dashboards, optimizing data visualization for better decision-making processes.

Manipulación de Datos | Descriptive Analytics and Data Transformation (2024)
Level: Advanced
Last update: March, 2024.

Collaborated in the extraction and manipulation of data for a telemarketing campaign in the banking sector.
Utilized R and its libraries, including dplyr, ggplot2, and tidyverse, to perform exploratory data analysis, transforming datasets and applying descriptive analytics to identify key customer behaviors.
Developed predictive models to forecast the success of telemarketing campaigns, identifying the most influential socio-economic factors on customer decisions.
Communicated findings through executive reports, employing data visualizations and clear insights to enhance decision-making processes.