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Data Science vs Data Analytics: Key Differences

Astera

Data Analytics is generally more focused and tends to answer specific questions based on past data. It’s about parsing data sets to provide actionable insights to help businesses make informed decisions. Summary statistics are also calculated to provide a quantitative description of the data.

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Information Marts: Enabling Agile, Scalable, and Accurate BI

Astera

Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. Traditional data warehouses with predefined data models and schemas are rigid, making it difficult to adapt to evolving data requirements.

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6 Benefits of Adopting a Cloud Data Warehouse for Your Organization

Astera

The 2020 Global State of Enterprise Analytics report reveals that 59% of organizations are moving forward with the use of advanced and predictive analytics. For this reason, most organizations today are creating cloud data warehouse s to get a holistic view of their data and extract key insights quicker.

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Cloud Data Warehouse: A Comprehensive Guide

Astera

The “cloud” part means that instead of managing physical servers and infrastructure, everything happens in the cloud environment—offsite servers take care of the heavy lifting, and you can access your data and analytics tools over the internet without the need for downloading or setting up any software or applications.

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What Is Embedded Analytics?

Insight Software

Strategic Objective Create an engaging experience in which users can explore and interact with their data. Requirement Filtering Users can choose the data that is important to them and get more specific in their analysis. Drilling Users can dig deeper and gain greater insights into the underlying data.