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Unfolding the Details of Hive in Hadoop

Pickl AI

Thus, making it easier for analysts and data scientists to leverage their SQL skills for Big Data analysis. It applies the data structure during querying rather than data ingestion. How Data Flows in Hive In Hive, data flows through several steps to enable querying and analysis.

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Accelerating time-to-insight with MongoDB time series collections and Amazon SageMaker Canvas

AWS Machine Learning Blog

MongoDB Atlas offers automatic sharding, horizontal scalability, and flexible indexing for high-volume data ingestion. Among all, the native time series capabilities is a standout feature, making it ideal for a managing high volume of time-series data, such as business critical application data, telemetry, server logs and more.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process. Data Ingestion : Involves raw data collection from origin and storage using architectures such as batch, streaming or event-driven.

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Unlocking generative AI for enterprises: How SnapLogic powers their low-code Agent Creator using Amazon Bedrock

AWS Machine Learning Blog

Data flow Here is an example of this data flow for an Agent Creator pipeline that involves data ingestion, preprocessing, and vectorization using Chunker and Embedding Snaps. He currently is working on Generative AI for data integration. The next paragraphs illustrate just a few.