Data Science Dojo

FEBRUARY 20, 2023

Apache Spark Apache Spark is an in-memory distributed computing platform. It provides a large cluster of clusters on a single machine. AWS SageMaker is useful for creating basic models, including regression, classification, and clustering. It has built-in support for machine learning.

Machine Learning 195

Machine Learning Machine Learning AWS Azure 195

Smart Data Collective

AUGUST 17, 2022

A hybrid cloud system is a cloud deployment model combining different cloud types, using both an on-premise hardware solution and a public cloud. You can also configure a cloud-based tool like AWS Glue to connect with your on-premise cloud hardware and establish a secure connection. Conclusion.

Apache Kafka 130

Apache Kafka ETL Data Lakes AWS 130

Applied Data Science

AUGUST 2, 2021

They bring deep expertise in machine learning , clustering , natural language processing , time series modelling , optimisation , hypothesis testing and deep learning to the team. They build production-ready systems using best-practice containerisation technologies, ETL tools and APIs.

Data Science 130

Data Science Data Scientist ML ML 130

phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. Vertical scaling refers to the increase in capability of existing computational resources, including CPU, RAM, or storage capacity. Data integrations and pipelines can also impact latency.

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Data Science Dojo

JULY 3, 2024

Machine Learning : Supervised and unsupervised learning algorithms, including regression, classification, clustering, and deep learning. Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Towards AI

FEBRUARY 11, 2025

Consider these common scenarios: A perfect validation script cant fix inconsistent data entry practices The most robust ETL pipeline cant resolve disagreements about business rules Real-time quality monitoring cant replace clear data ownership. Managing these costs efficiently is crucial to sustaining AI advancements.

Data Quality 59

Data Quality Data Engineering Data Engineer Data Engineering 59

Dataconomy

FEBRUARY 23, 2023

This involves working with various tools and technologies, such as ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform) processes, to move data from its source to its destination. Cloud computing: Cloud computing provides a scalable and cost-effective solution for managing and processing large volumes of data.

Data Engineer 91

Data Engineer Data Engineering Data Engineering Data Engineering 91