Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. 5 Key Comparisons in Different Apache Kafka Architectures. 5 Key Comparisons in Different Apache Kafka Architectures.

Apache Kafka 107

Apache Kafka ETL Data Lakes AWS 107

phData

MAY 3, 2024

How Snowflake Helps Achieve Real-Time Analytics Snowflake is the ideal platform to achieve real-time analytics for several reasons, but two of the biggest are its ability to manage concurrency due to the multi-cluster architecture of Snowflake and its robust connections to 3rd party tools like Kafka. Looking for additional help?

Apache Kafka 52

Apache Kafka Analytics Analytics ETL 52

Pickl AI

JULY 24, 2023

Data warehousing and ETL (Extract, Transform, Load) procedures frequently involve batch processing. Utilising data streaming platforms such as Apache Kafka, Apache Flink, or Apache Spark Streaming, data is gathered from many sources and processed in real-time or close to real-time.

Internet of Things 52

Internet of Things Apache Kafka ETL Azure 52

The MLOps Blog

MARCH 15, 2023

Typical examples include: Airbyte Talend Apache Kafka Apache Beam Apache Nifi While getting control over the process is an ideal position an organization wants to be in, the time and effort needed to build such systems are immense and frequently exceeds the license fee of a commercial offering.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

AWS Machine Learning Blog

JANUARY 6, 2023

TR used AWS Glue DataBrew and AWS Batch jobs to perform the extract, transform, and load (ETL) jobs in the ML pipelines, and SageMaker along with Amazon Personalize to tailor the recommendations. Then the events are ingested into TR’s centralized streaming platform, which is built on top of Amazon Managed Streaming for Kafka (Amazon MSK).

AWS 67

AWS Data Warehouse ML ML 67

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 Engineer Data Engineering Data Engineering 52

Data Science Blog

JUNE 27, 2023

In practical implementation, the Kappa architecture is commonly deployed using Apache Kafka or Kafka-based tools. Applications can directly read from and write to Kafka or an alternative message queue tool. It offers the advantage of having a single ETL platform to develop and maintain.

Big Data 130

Big Data Big Data Apache Kafka Database 130