Knowledge Base

What is Rosetta Stone?

In the vast and varied landscape of data management, every company collects and stores data in its unique "language" - a format that can be quite distinct and specialized, catering to internal systems, programs, and analysts. This diversity in data storage and representation languages has historically posed a significant barrier to efficient data transactions, requiring considerable effort and time to decode and translate data for external use.

The Solution: Rosetta Stone

Narrative’s Rosetta Stone emerges as a groundbreaking solution to this challenge, acting as a universal translator for data. It effectively translates data from a multitude of languages into one universally understood format. This is achieved by taking data in its native format from each provider and normalizing it, enabling the combination and comparison of data from various sources seamlessly.

Example of Normalization

Consider the scenario where different data providers record dates in formats like “mm/dd/yyyy,” “mm-dd-yyyy,” and “yyyy-mm-dd.” Rosetta Stone identifies all such entries as date data and normalizes them into a consistent format, such as “mm-dd-yyyy.” This standardization simplifies data ingestion and analysis processes, allowing systems to easily recognize and interpret data from any provider.

Mapping Proccess

Rosetta Stone leverage a combination of machine learning and human curation to map data from a wide variety of sources to a common schema. This process is iterative, ongoing, and seamless to the suer as new data sources are added to the platform. This mapping process, in the absense of Rosetta Stone, would be a manual process that would require significant time and effort that can be better spent on other tasks.

How Rosetta Stone Works

Rosetta Stone can be likened to a sophisticated "query planner." Users on the Narrative data collaboration platform can specify the dataset they need, and Rosetta Stone orchestrates the retrieval of this data across various suppliers, tables, and formats. This ensures that the resulting dataset is normalized across all required fields, making it readily usable for the buyer.

Real-world Application

In the context of weather data, for example, Rosetta Stone can harmonize information collected in different formats by multiple suppliers into a single, coherent dataset. This allows buyers to easily understand and apply the data to their projects without needing to navigate the intricacies of the original storage formats.

Utilizing Rosetta Stone on Narrative’s Platform

Rosetta Stone is instrumental in establishing Narrative as a leading data collaboration platform. It enables buyers to efficiently scale their data acquisition efforts, purchasing data from a wide array of suppliers simultaneously. This capability not only breaks down traditional barriers in the data economy but also significantly accelerates the process of data acquisition and utilization.