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 130

Apache Kafka ETL Data Lakes AWS 130

IBM Journey to AI blog

JANUARY 8, 2024

They often use Apache Kafka as an open technology and the de facto standard for accessing events from a various core systems and applications. IBM provides an Event Streams capability build on Apache Kafka that makes events manageable across an entire enterprise.

EDA 92

EDA Apache Kafka Clustering Data Governance 92

AWS Machine Learning Blog

OCTOBER 9, 2024

To learn more, see the documentation. To learn more, see the documentation. To learn more, see the documentation. To learn more, see the blog post , watch the introductory video , or see the documentation. There are no additional costs to using Redshift ML for anomaly detection. Choose Delete.

AWS 83

AWS ML ML Data Quality 83

IBM Journey to AI blog

NOVEMBER 9, 2023

Apache Kafka is a high-performance, highly scalable event streaming platform. To unlock Kafka’s full potential, you need to carefully consider the design of your application. It’s all too easy to write Kafka applications that perform poorly or eventually hit a scalability brick wall. So, what can you do?

Apache Kafka 78

Apache Kafka Algorithm Clustering 78

IBM Journey to AI blog

JULY 12, 2024

IBM® Event Automation’s event endpoint management capability makes it easy to describe and document your Kafka topics (event sources) according to the open source AsyncAPI Specification. Why is this important? AsyncAPI already fuels clarity, standardization, interoperability, real-time responsiveness and beyond.

Apache Kafka 40

Apache Kafka Clustering 40

IBM Journey to AI blog

AUGUST 22, 2024

In recognizing the benefits of event-driven architectures, many companies have turned to Apache Kafka for their event streaming needs. Apache Kafka enables scalable, fault-tolerant and real-time processing of streams of data—but how do you manage and properly utilize the sheer amount of data your business ingests every second?

EDA 40

EDA Apache Kafka Clustering 40

DagsHub

OCTOBER 23, 2024

For instance, if the collected data was a text document in the form of a PDF, the data preprocessing—or preparation stage —can extract tables from this document. The pipeline in this stage can convert the document into CSV files, and you can then analyze it using a tool like Pandas. Unstructured.io

Machine Learning 52

Machine Learning Machine Learning AI AI 52