This project aimed to centralize and automate the collection of market data, contracts, financial figures, and student information from various countries for the Sanillana's headquarters. Previously, the process was heavily manual, prone to errors, and time-consuming.
By developing a standardized data structure, automating data transformations, and creating an interactive dashboards portal, the project significantly improved the accuracy of reporting and decision-making. As a result, the data centralization process was streamlined, reducing manual errors and the time spent on data consolidation.
Before Implementation
Data inconsistencies across different file structures, undefined categories, and formatting discrepancies.
Time-consuming manual consolidation due to differing data structures.
Delays in data collection hindered quick decision-making.
Key Improvements
Standardized data structure across all countries, unifying categories, and formats.
Automated data transformation pipeline, minimizing manual intervention.
Real-time data accessibility via a consolidated data warehouse.
Project Overview
1.
Data Analysis
We started by analyzing the data from multiple countries, identifying key discrepancies in formats, and preparing a plan to consolidate these differences. This also involved defining communication channels and work methodologies.
2.
Data Centralization
After reviewing the different data sources, we created a standardized data structure for all countries. We developed a common table in BigQuery, consolidating all relevant variables like countries, sectors, markets, contracts, and products.
3.
Data Modeling
The consolidated data was then modeled in BigQuery. We created a first version of the interactive dashboard in Power BI, enabling real-time data refresh and visual insights, including KPIs and trend charts.
4.
KPI Analysis
We cleaned and corrected data inconsistencies, such as different numeric formats. Simultaneously, we conducted a thorough KPI analysis to ensure the final dashboard would meet the client's needs, providing clear and actionable insights.
Azure
Excel Sheets
Power BI
Python
Technologies used
Francisco Ortiz
Inteligencia de Negocio Corporativo - Santillana
"We are extremely satisfied with the results of this project. The transition from a manual, time-consuming data collection process to an automated, centralized solution has drastically improved our ability to make informed decisions. The Datakimia's professionalism and expertise were evident throughout the project, and we would highly recommend their services."
