Cloudera

MAY 30, 2024

By leveraging the flexibility of a data lake and the structured querying capabilities of a data warehouse, an open data lakehouse accommodates raw and processed data of various types, formats, and velocities.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

AltexSoft

JULY 18, 2023

It has in-memory computing capabilities to deliver speed, a generalized execution model to support various applications, and Java, Scala, Python, and R APIs. Spark Streaming enhances the core engine of Apache Spark by providing near-real-time processing capabilities, which are essential for developing streaming analytics applications.

Big Data 52

Big Data Data Process Process Hadoop 52

Workfall

JUNE 27, 2023

It enables the collection of data from diverse platforms in real-time, organizing it into consolidated feeds while providing comprehensive metrics for monitoring. As a distributed data storage system, Kafka has been meticulously optimized to handle the continuous flow of streaming data generated by numerous sources.

Kafka 75

Kafka Architecture AWS Transportation 75

Knowledge Hut

JUNE 26, 2023

If you want to break into the field of data engineering but don't yet have any expertise in the field, compiling a portfolio of data engineering projects may help. Data pipeline best practices should be shown in these initiatives. Source Code: Finnhub API with Kafka for Real-Time Financial Market Data Pipeline 3.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Knowledge Hut

JUNE 30, 2023

Key Benefits and Takeaways: Understand data intake strategies and data transformation procedures by learning data engineering principles with Python. Investigate alternative data storage solutions, such as databases and data lakes. Key Benefits and Takeaways: Learn the core concepts of big data systems.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

MAY 14, 2024

Apache ORC (Optimized Row Columnar) : In 2013, ORC was developed for the Hadoop ecosystem to improve the efficiency of data storage and retrieval. This development was crucial for enabling both batch and streaming data workflows in dynamic environments, ensuring consistency and durability in big data processing.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

ProjectPro

JANUARY 31, 2023

This process involves data collection from multiple sources, such as social networking sites, corporate software, and log files. Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop Relational Database AWS 52