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Prescriptive AI: The Smart Decision-Maker for Healthcare, Logistics, and Beyond

Unite.AI

Prescriptive AI relies on several essential components that work together to turn raw data into actionable recommendations. The process begins with data ingestion and preprocessing, where prescriptive AI gathers information from different sources, such as IoT sensors, databases, and customer feedback.

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Real-Time App Performance Monitoring with Apache Pinot

Analytics Vidhya

Apache Pinot, an open-source OLAP datastore, offers the ability to handle real-time data ingestion and low-latency querying, making it […] The post Real-Time App Performance Monitoring with Apache Pinot appeared first on Analytics Vidhya.

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What is Data Ingestion? Understanding the Basics

Pickl AI

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. This is where data ingestion comes in.

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The Three Big Announcements by Databricks AI Team in June 2024

Marktechpost

This new version enhances the data-focused authoring experience for data scientists, engineers, and SQL analysts. The updated Notebook experience features a sleek, modern interface and powerful new functionalities to simplify coding and data analysis.

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Skip Levens, Marketing Director, Media & Entertainment, Quantum – Interview Series

Unite.AI

What are the primary challenges organizations face when implementing AI for unstructured data analysis, and how does Quantum help mitigate these challenges? Organizations must completely reimagine their approach to storage, as well as data and content management as a whole.

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A Beginner’s Guide to Data Warehousing

Unite.AI

Traditional Data Warehouse Architecture Bottom Tier (Database Server): This tier is responsible for storing (a process known as data ingestion ) and retrieving data. The data ecosystem is connected to company-defined data sources that can ingest historical data after a specified period.

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Meet MegaParse: An Open-Source AI Tool for Parsing Various Types of Documents for LLM Ingestion

Marktechpost

In the evolving landscape of artificial intelligence, language models are becoming increasingly integral to a variety of applications, from customer service to real-time data analysis. One key challenge, however, remains: preparing documents for ingestion into large language models (LLMs). Check out the GitHub Page.

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