AI News

SEPTEMBER 29, 2024

Here are a few key reasons: The variety and volume of data will continue to grow, requiring the database to handle diverse data types—structured, unstructured, and semi-structured—at scale. Selecting a database that can manage such variety without complex ETL processes is important.

Big Data 297

Big Data ETL Generative AI Data Ingestion 297

Unite.AI

DECEMBER 5, 2023

These can include structured databases, log files, CSV files, transaction tables, third-party business tools, sensor data, etc. The pipeline ensures correct, complete, and consistent data. Metadata: Metadata is data about the data. Metadata: Metadata is data about the data.

Metadata 162

Metadata Big Data ETL Data Mining 162

IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Perform data quality monitoring based on pre-configured rules.

Data Quality 130

Data Quality Metadata ETL Big Data 130

AWS Machine Learning Blog

MAY 5, 2023

The following figure shows an example diagram that illustrates an orchestrated extract, transform, and load (ETL) architecture solution. For example, searching for the terms “How to orchestrate ETL pipeline” returns results of architecture diagrams built with AWS Glue and AWS Step Functions. join(", "), }; }).catch((error)

Metadata 110

Metadata ETL ML Data Ingestion 110

AWS Machine Learning Blog

APRIL 4, 2024

Prerequisites To implement this solution, you need the following: Historical and real-time user click data for the interactions dataset Historical and real-time news article metadata for the items dataset Ingest and prepare the data To train a model in Amazon Personalize, you need to provide training data.

ETL 104

ETL Auto-complete Metadata Data Ingestion 104

Pickl AI

JULY 30, 2024

Summary: Apache NiFi is a powerful open-source data ingestion platform design to automate data flow management between systems. Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. FlowFile At the core of NiFi’s architecture is the FlowFile.

Data Ingestion 52

Data Ingestion ETL Big Data Data Integration 52

The MLOps Blog

JANUARY 26, 2024

A feature store typically comprises a feature repository, a feature serving layer, and a metadata store. It can also transform incoming data on the fly. The metadata store manages the metadata associated with each feature, such as its origin and transformations. Typically, these activities are collectively called “ MLOps.”

Machine Learning 72

Machine Learning Metadata ML Python 72