Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data. They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. What is data engineering?

Big Data 91

Big Data Big Data Data Engineering Data Engineer 91

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. You can review the recommendations and augment rules from over 25 included data quality rules.

AWS 96

AWS ML ML Data Quality 96

Data Science Blog

JUNE 27, 2023

The batch views within the Lambda architecture allow for the application of more complex or resource-intensive rules, resulting in superior data quality and reduced bias over time. On the other hand, the real-time views provide immediate access to the most current data.

Big Data 130

Big Data Big Data Apache Kafka Database 130

Mlearning.ai

MAY 16, 2023

Data engineering is a rapidly growing field that designs and develops systems that process and manage large amounts of data. There are various architectural design patterns in data engineering that are used to solve different data-related problems.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

DagsHub

OCTOBER 23, 2024

General Purpose Tools These tools help manage the unstructured data pipeline to varying degrees, with some encompassing data collection, storage, processing, analysis, and visualization. DagsHub's Data Engine DagsHub's Data Engine is a centralized platform for teams to manage and use their datasets effectively.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

DagsHub

JANUARY 14, 2025

Uncertain examples are chosen for expert labelling and then fed-back into the training dataset to undergo additional active learning iterations, while the trained model generates duplicate/non-duplicate predictions on unlabeled data. Tools like Apache Kafka and Apache Flink can be configured for this purpose.

Machine Learning 52

Machine Learning Machine Learning Clustering Algorithm 52