Dataconomy

SEPTEMBER 4, 2023

Key features of cloud analytics solutions include: Data models , Processing applications, and Analytics models. Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence.

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Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Microsoft Power BI has been the leader in the analytics and business intelligence platforms category for several years running.

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Power BI Analytics Analytics Azure 84

Cambridge Intelligence

OCTOBER 19, 2023

That’s why our data visualization SDKs are database agnostic: so you’re free to choose the right stack for your application. Multi-model databases combine graphs with two other NoSQL data models – document and key-value stores. Transactional, analytical, or both…?

Database 59

Database Azure SQL Analytics 59

Pickl AI

JUNE 18, 2024

Summary: This blog dives into the most promising Power BI projects, exploring advanced data visualization, AI integration, IoT & blockchain analytics, and emerging technologies. Discover best practices for successful implementation and propel your organization towards data-driven success.

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Power BI Data Analysis Data Analysis Data Visualization 52

Data Science Blog

JULY 23, 2023

Companies use Business Intelligence (BI), Data Science , and Process Mining to leverage data for better decision-making, improve operational efficiency, and gain a competitive edge. One of this aspect is the cloud architecture for the realization of Data Mesh. Each applications has its own data model.

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Data Science Azure Power BI Business Intelligence 246

phData

JULY 18, 2023

CDWs are designed for running large and complex queries across vast amounts of data, making them ideal for centralizing an organization’s analytical data for the purpose of business intelligence and data analytics applications. It should also enable easy sharing of insights across the organization.

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Data Warehouse Analytics Analytics SQL 52