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Apache Kafka use cases: Driving innovation across diverse industries

IBM Journey to AI blog

Apache Kafka is an open-source , distributed streaming platform that allows developers to build real-time, event-driven applications. With Apache Kafka, developers can build applications that continuously use streaming data records and deliver real-time experiences to users. How does Apache Kafka work?

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Transitioning off Amazon Lookout for Metrics 

AWS Machine Learning Blog

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. To use this feature, you can write rules or analyzers and then turn on anomaly detection in AWS Glue ETL.

AWS 86
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Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

AWS Machine Learning Blog

Streaming ingestion – An Amazon Kinesis Data Analytics for Apache Flink application backed by Apache Kafka topics in Amazon Managed Streaming for Apache Kafka (MSK) (Amazon MSK) calculates aggregated features from a transaction stream, and an AWS Lambda function updates the online feature store.

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Big data engineering simplified: Exploring roles of distributed systems

Data Science Dojo

Amazon S3: Amazon Simple Storage Service (S3) is a scalable object storage service provided by Amazon Web Services (AWS). Spark provides a high-level API in multiple languages like Scala, Python, Java, and SQL, making it accessible to a wide range of developers.

Big Data 195
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How Thomson Reuters delivers personalized content subscription plans at scale using Amazon Personalize

AWS Machine Learning Blog

The rules in this engine were predefined and written in SQL, which aside from posing a challenge to manage, also struggled to cope with the proliferation of data from TR’s various integrated data source. TR wanted to take advantage of AWS managed services where possible to simplify operations and reduce undifferentiated heavy lifting.

AWS 79
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Discover the Most Important Fundamentals of Data Engineering

Pickl AI

Various types of storage options are available, including: Relational Databases: These databases use Structured Query Language (SQL) for data management and are ideal for handling structured data with well-defined relationships. SQL SQL is crucial for querying and managing relational databases.

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Comparing Tools For Data Processing Pipelines

The MLOps Blog

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. Cons Limited connectors.