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Unlocking Data Storage: The Traditional Data Warehouse vs. Cloud Data Warehouse

Sisense

While the architecture of traditional data warehouses and cloud data warehouses does differ, the ways in which data professionals interact with them (via SQL or SQL-like languages) is roughly the same. Scaling the warehouse as business analytics needs grow is as simple as clicking a few buttons (and in some cases, it is even automatic).

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Data Model Development Using Jinja

Sisense

Every aspect of analytics is powered by a data model. A data model presents a “single source of truth” that all analytics queries are based on, from internal reports and insights embedded into applications to the data underlying AI algorithms and much more. Designers, engineers, and analysts see data in different ways.