Clean Data, Data Observability and SQL

Data Quality Framework: What It Is, Components, and Implementation

DagsHub

AUGUST 23, 2024

Data quality is crucial across various domains within an organization. For example, software engineers focus on operational accuracy and efficiency, while data scientists require clean data for training machine learning models. Without high-quality data, even the most advanced models can't deliver value.

Data Quality

Data Quality Data Governance Machine Learning Machine Learning

Build Data Pipelines: Comprehensive Step-by-Step Guide

Pickl AI

JULY 8, 2024

Organisations leverage diverse methods to gather data, including: Direct Data Capture: Real-time collection from sensors, devices, or web services. Database Extraction: Retrieval from structured databases using query languages like SQL. Aggregation: Summarising data into meaningful metrics or aggregates.

Data Pipeline

Data Pipeline Data Quality Database Apache Kafka

Data Science Current

Data Quality Framework: What It Is, Components, and Implementation

Build Data Pipelines: Comprehensive Step-by-Step Guide

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