From manual to automation: Starbucks consolidates 1B+ rows of multi-country sales data from Nielsen
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From manual to automation: Starbucks consolidates 1B+ rows of multi-country sales data from Nielsen
Like most global brands, Starbucks gets supermarket sales data from Nielsen to understand consumer trends, track regional sales performance, and assess the impact of promotions – both for Starbucks and its competitors.
Starbucks used to spend 100+ hours each month unifying and transforming country-specific sales data into static spreadsheets and PowerPoints.
The data transformation challenges included processing large data sets, synchronizing varying, country-specific data schedules and complex data hierarchies, and addressing quality issues in data cleanup and validation.
Mammoth’s ready-made solution tackles those relatively common but painful challenges effortlessly.
The platform allows Starbucks to load and transform large, intricate datasets efficiently. Now, Starbucks automatically synchronizes Nielsen data across countries, ensuring accurate country comparisons and timely refreshes. Also, Mammoth brings easy data exploration to non-technical users, unveiling previously undiscovered patterns crucial for strategic decision-making.
With Mammoth, Starbucks can make informed decisions swiftly, foster trust in its data-driven insights, and maintain flexibility in adapting to changing data sources for sustained business growth.
Mammoth allows non-technical users to set up automated data cleaning and transformation rules that are visible to the whole team and editable at any time.
The transformative solution delivers vital benefits:
Quicker report generation: Accelerating the reporting process translates to more timely decision-making for Starbucks.
Transparency: Visible, understandable data cleaning and transformation rules enhance trust in the analytical outcomes, providing Starbucks with a solid foundation for strategic moves.
Scalability: Mammoth empowers Starbucks to scale its analytics operations efficiently, accommodating its evolving needs.
Separation of business layer and data source: The ease of combining multiple sources in one place allows Starbucks to consider additional data vendors in the future, fostering flexibility and adaptability.
Does your team spend time on unifying and transforming data? Sign up for Mammoth’s product and learn how to get rid of repetitive data cleaning work!