Businesses are working with an ever-growing number of data sources across platforms like AWS, Azure, GCP, Snowflake, and Databricks. However, the complexities of managing and aligning these disparate datasets pose significant challenges, particularly during the transformation step of ETL (Extract, Transform, Load). Manual transformation is labor-intensive, prone to errors, and a bottleneck to unlocking real-time collaboration and insights.
Enter Narrative’s Rosetta Stone, a platform designed to solve these challenges by offering AI-based schema harmonization. Rosetta Stone automates the process of aligning datasets from different sources, ensuring they are ready for seamless collaboration and real-time insights.
What makes Rosetta Stone especially compelling is its ease of adoption: syncing your schema comes at no cost, and once your data is synced, unlocking automated transformations and collaboration becomes effortless. With Rosetta Stone, businesses can transform how they manage data and collaborate, moving from manual processes to automated, scalable workflows that reduce operational costs and speed up time-to-value.
The Pain of Manual Data Transformation
Traditional ETL workflows require businesses to manually clean, align, and standardize data from various sources. This is especially challenging when dealing with inconsistent data schemas, as businesses must dedicate significant time and resources to ensuring that data from one system matches the structure of another. Key pain points include:
- High Costs and Resource Drain: Manual transformation is time-consuming and costly, requiring specialized skills and ongoing maintenance.
- Inconsistent Data: Different data sources may use different schemas, resulting in fragmented data that needs to be painstakingly aligned.
- Delayed Insights: The manual transformation process slows down data processing, delaying insights and reducing a company’s agility in a competitive market.
Rosetta Stone’s AI-based harmonization of schemas eliminates these issues by automatically mapping and standardizing data from multiple sources, allowing businesses to collaborate with, high-quality data.