Data Science Dojo

OCTOBER 31, 2024

Strong analytical skills and the ability to work with large datasets are critical, as is familiarity with data modeling and ETL processes. Programming Questions Data science roles typically require knowledge of Python, SQL, R, or Hadoop. Prepare to discuss your experience and problem-solving abilities with these languages.

Data Science 195

Data Science Data Scientist Machine Learning Machine Learning 195

AWS Machine Learning Blog

FEBRUARY 21, 2025

Rockets legacy data science environment challenges Rockets previous data science solution was built around Apache Spark and combined the use of a legacy version of the Hadoop environment and vendor-provided Data Science Experience development tools. This also led to a backlog of data that needed to be ingested.

Data Science 85

Data Science AWS Hadoop Data Scientist 85

Pickl AI

SEPTEMBER 19, 2024

Summary: This article compares Spark vs Hadoop, highlighting Spark’s fast, in-memory processing and Hadoop’s disk-based, batch processing model. Introduction Apache Spark and Hadoop are potent frameworks for big data processing and distributed computing. What is Apache Hadoop? What is Apache Spark?

Hadoop 52

Hadoop Big Data Big Data Clustering 52

Data Science Dojo

JULY 3, 2024

Big Data Technologies : Handling and processing large datasets using tools like Hadoop, Spark, and cloud platforms such as AWS and Google Cloud. Data Engineering : Building and maintaining data pipelines, ETL (Extract, Transform, Load) processes, and data warehousing.

Data Science 150

Data Science Machine Learning Machine Learning Data Visualization 150

Mlearning.ai

MAY 16, 2023

ETL Design Pattern The ETL (Extract, Transform, Load) design pattern is a commonly used pattern in data engineering. ETL Design Pattern Here is an example of how the ETL design pattern can be used in a real-world scenario: A healthcare organization wants to analyze patient data to improve patient outcomes and operational efficiency.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

IBM Journey to AI blog

AUGUST 29, 2024

Event-driven businesses across all industries thrive on real-time data, enabling companies to act on events as they happen rather than after the fact. This is where Apache Flink shines, offering a powerful solution to harness the full potential of an event-driven business model through efficient computing and processing capabilities.

Apache Kafka 45

Apache Kafka Hadoop ETL Data Pipeline 45

ODSC - Open Data Science

SEPTEMBER 27, 2023

Cost-Efficiency By leveraging cost-effective storage solutions like the Hadoop Distributed File System (HDFS) or cloud-based storage, data lakes can handle large-scale data without incurring prohibitive costs. Interested in attending an ODSC event? Learn more about our upcoming events here.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98