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Data virtualization

Dataconomy

Mechanics of data virtualization Understanding how data virtualization works reveals its benefits in organizations. Middleware role Data virtualization often functions as middleware that bridges various data models and repositories, including cloud data lakes and on-premise warehouses.

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Data Mesh Architecture on Cloud for BI, Data Science and Process Mining

Data Science Blog

A Data Product can take various forms, depending on the domain’s requirements and the data it manages. It could be a curated dataset, a machine learning model, an API that exposes data, a real-time data stream, a data visualization dashboard, or any other data-related asset that provides value to the organization.

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Beyond data: Cloud analytics mastery for business brilliance

Dataconomy

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Here are some of the key types of cloud analytics: Descriptive analytics: This type focuses on summarizing historical data to provide insights into what has happened in the past.

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Business Intelligence for Fairs, Congresses and Exhibitions

Smart Data Collective

If you occasionally run business stands in fairs, congresses and exhibitions, business stands designers can incorporate business intelligence to aid in better business and client data collection. Business intelligence tools can include data warehousing, data visualizations, dashboards, and reporting.

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Self-Service Analytics for Google Cloud, now with Looker and Tableau

Tableau

Leveraging Looker’s semantic layer will provide Tableau customers with trusted, governed data at every stage of their analytics journey. With its LookML modeling language, Looker provides a unique, modern approach to define governed and reusable data models to build a trusted foundation for analytics.

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BI Tools Comparison to Improve Data Clarity | Women in Big Data

Women in Big Data

It integrates seamlessly with a wide range of data sources like Excel, Azure and SQL server, Salesforce, SAP Hana, IBM Netezza and CDP which makes it a compelling choice for businesses that have already invested in the Microsoft ecosystem. It allows users to create highly customizable and visually appealing reports.

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Where Does Fivetran Fit into The Modern Data Stack?

phData

Over the past few decades, the corporate data landscape has changed significantly. The shift from on-premise databases and spreadsheets to the modern era of cloud data warehouses and AI/ LLMs has transformed what businesses can do with data. Data modeling, data cleanup, etc.