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Data Mesh

Data Mesh Architecture Through Different Perspectives

We previously wrote how the data mesh architecture rose as an answer to the problems of the monolithic centralized data model. To recap, in the centralized data models, ETL or ELT data pipelines collect data from various enterprise data sources and ingest it into a single central data lake or data warehouse. Data consumers and business intelligence tools access the data from the central storage to drive insights and inform decision-making.

Choreograph Uses Snowflake to Build a Data Mesh to Enhance Data Sharing Across WPP's Vast Enterprise

In order to satisfy client expectations, advertising and media agencies must aggregate, centralize, and mobilize data to augment customer insights, enhance campaigns, and measure attribution. Doing that well is no easy task. For WPP, the world’s largest advertising and media consulting company, that task is made more complicated by the vast amounts of data it owns that is spread over its large network of operating companies (Op-Cos).