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Gartner estimates that by 2022, 75% of all databases will be deployed or migrated to a cloud data platform. This trend is driving sweeping change within enterprise analytics infrastructures, opening up new challenges and possibilities for BI and data science programs. The role of semantic layer technology to support agility, consistency, and analytics performance becomes critical with this shift toward cloud data infrastructure. AtScale deployments on leading cloud data platforms have increased 89% during the past 12 months.
“We have seen cloud-first customers looking at an AtScale semantic layer as the ‘central nervous system’ for their business intelligence and data science programs,” said Christopher Lynch, Executive Chairman and CEO of AtScale. “CloudStart simplifies AtScale implementation on leading cloud platforms and accelerates time-to-value.”
AtScale CloudStart is immediately available for Snowflake, Microsoft Azure Synapse SQL, Google BigQuery, Amazon Redshift, and DataBricks. Customers can leverage this offering to connect cloud data sources to BI tools including Tableau, Excel, Looker and Power BI (leveraging the recently announced Live Query support for Power BI). Accompanying services packages support training and rapid onboarding for fast time to value.
“Partnering with AtScale and Snowflake radically improved our BI program and client experience,” said Greg Mabrito, Director of Data and Analytics at Slickdeals. “We went from a legacy, on-premise, largely manual data analytics pipeline to a robust, flexible and highly scalable platform. This transformation has unlocked tremendous business value for our internal and external customers.”
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As enterprise data moves to the cloud, analytics teams are challenged to ensure performance and manage costs while capturing the value of democratizing data. AtScale’s semantic layer eliminates the friction of moving BI, artificial intelligence and machine learning workloads to the cloud. By leveraging a single source of enterprise business metrics, organizations can drive data literacy and self-service BI initiatives while aligning business intelligence and data science teams.
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