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Top 10 Al Agent Use Cases Across Industries

Artificial intelligence has transformed the way businesses operate, and AI agents are at the forefront of this revolution. An AI agent is a software system capable of performing tasks, making decisions, and interacting with humans or other systems with minimal human intervention

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Business-Driven Approach to Sigma Access Control

For data-driven organizations, properly managing user access to analytics platforms is essential to safeguard sensitive information and maintain governance standards. At our data platform services company, we implemented robust Sigma access control to ensure that only authorized users could access specific data folders and reports

Website:https://dataplatr.com/blog/dat....a-science?utm_source

What is data science?

Data science is the study of data to extract meaningful insights for business. It is an approach that combines principles and practices from the fields of mathematics, statistics, artificial intelligence, and computer engineering to analyze and to drive business decision-making. This analysis helps data scientists to ask and answer questions like what happened, why it happened, what will happen, and what can be done with the results.

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What is Data Lakehouse Architecture?

Data lakehouse architecture allows organizations to manage both structured and unstructured data within a single, scalable system. It supports diverse use cases like business reporting, real-time analytics, and machine learning, all within a single system. This flexibility is made possible through five foundational layers that work together to collect, store, manage, and deliver data efficiently.

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What Is a Data Lakehouse? Benefits, Features & Platforms

A data lakehouse is a system that brings together the best features of both data lakes and data warehouses. It allows businesses to store all kinds of data, structured like tables or unstructured like images or logs, in one place.
In the past, companies used data lakes to store raw data and data warehouses for organized, ready-to-use data. But this often caused problems like data duplication and slow workflows.