Dmesh algorithm1/3/2024 ![]() ![]() Underpinning this desire for democratization and scalability is the realization that your current data architecture (in many cases, a siloed data warehouse or a data lake with some limited real-time streaming capabilities) may not be meeting your needs.įortunately, teams seeking a new lease on data need look no further than a data mesh, an architecture paradigm that’s taking the industry by storm. Most of all, however, your entire data team wishes there were an easier way to manage the growing needs of your organization, from fielding the never-ending stream of ad hoc queries to wrangling disparate data sources through a central ETL pipeline. ![]() Or maybe your CDO spearheaded a cross-functional initiative to educate teams on data management best practices and your CTO invested in a data engineering group. Your boss was one of the first in the industry to see the potential in Snowflake and Looker. Your company, for one, views data as a driver of innovation. In the age of self-service business intelligence, nearly every company considers themselves a data-first company, but not every company is treating their data architecture with the level of democratization and scalability it deserves. But what is a data mesh and why should you build one? Inquiring minds want to know. Ask anyone in the data industry what’s hot these days and chances are “data mesh” will rise to the top of the list. ![]()
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