Challenges:
Interconnection issues: Each business unit employed different technologies which were not interoperable.
No global data: Unreliable, isolated data made it impossible to get general insights.
Lack of technical know-how: Efficiency, self-serve, and minimal burden were a must.
Stale Data: everyone worked with old data that took weeks to produce.
Solution:
Technologies Adopted: Fivetran, Snowflake, DBT, Dataiku.
Dedicated Data Teams: Delivered results quickly and safely.
Results:
– 900+ automatizations, making thousands of repetitive task all over the company completely unnecessary, freeing time for more productive work, dramatically improving data quality y allowing fixing
– LLM for non-technical employees who can now leverage deep data analitics with natural language.
– Development of own data apps: Testing how different variables or changing supplies affects production yields.
– Global view across multiple companies with different systems.
– All Data Scientists and BI can now focus on insights of getting value with good valid and abundant data.
