AWS Machine Learning Blog

SEPTEMBER 11, 2024

In this post, we demonstrate how to build a robust real-time anomaly detection solution for streaming time series data using Amazon Managed Service for Apache Flink and other AWS managed services. It offers an AWS CloudFormation template for straightforward deployment in an AWS account.

AWS 121

AWS ML ML Apache Kafka 121

Pickl AI

FEBRUARY 23, 2025

Best Big Data Tools Popular tools such as Apache Hadoop, Apache Spark, Apache Kafka, and Apache Storm enable businesses to store, process, and analyse data efficiently. Statistics : According to AWS reports, EMR reduces the time required for Big Data processing tasks by up to 90% compared to traditional methods.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

Pickl AI

MARCH 19, 2025

Python, SQL, and Apache Spark are essential for data engineering workflows. Real-time data processing with Apache Kafka enables faster decision-making. Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data. Which cloud-based data engineering tools are most popular?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

AWS Machine Learning Blog

JANUARY 6, 2023

TR wanted to take advantage of AWS managed services where possible to simplify operations and reduce undifferentiated heavy lifting. 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.

AWS 95

AWS Data Warehouse ML ML 95

Data Science Dojo

JULY 24, 2023

Amazon S3: Amazon Simple Storage Service (S3) is a scalable object storage service provided by Amazon Web Services (AWS). Unlike traditional batch processing, where data is processed in fixed intervals, stream processing enables organizations to gain insights and respond to events as they happen in real-time.

Big Data 195

Big Data Big Data Data Engineering Data Engineering 195

AWS Machine Learning Blog

APRIL 19, 2023

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.

ML 98

ML ML Apache Kafka SQL 98

ODSC - Open Data Science

FEBRUARY 6, 2024

Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer. Interested in attending an ODSC event? Learn more about our upcoming events here. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

SEPTEMBER 18, 2024

It utilises Amazon Web Services (AWS) as its main data lake, processing over 550 billion events daily—equivalent to approximately 1.3 Data in Motion Technologies like Apache Kafka facilitate real-time processing of events and data, allowing Netflix to respond swiftly to user interactions and operational needs.

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

Pickl AI

NOVEMBER 4, 2024

Among these tools, Apache Hadoop, Apache Spark, and Apache Kafka stand out for their unique capabilities and widespread usage. Apache Hadoop Hadoop is a powerful framework that enables distributed storage and processing of large data sets across clusters of computers.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

JULY 20, 2023

Diagnostic Analytics Projects: Diagnostic analytics seeks to determine the reasons behind specific events or patterns observed in the data. 3. Predictive Analytics Projects: Predictive analytics involves using historical data to predict future events or outcomes. Root cause analysis is a typical diagnostic analytics task.

Analytics 40

Analytics Analytics Big Data Big Data 40

DagsHub

OCTOBER 23, 2024

Apache Kafka Apache Kafka is a distributed event streaming platform for real-time data pipelines and stream processing. Kafka is highly scalable and ideal for high-throughput and low-latency data pipeline applications. It allows unstructured data to be moved and processed easily between systems.

Machine Learning 52

Machine Learning Machine Learning Data Lakes AI 52

DagsHub

APRIL 7, 2024

Flexibility: Airflow was designed with batch workflows in mind; it was not meant for permanently running event-based workflows. Also, while it is not a streaming solution, we can still use it for such a purpose if combined with systems such as Apache Kafka. Miscellaneous Workflows are created as directed acyclic graphs (DAGs).

Machine Learning 59

Machine Learning Machine Learning ML ML 59

The MLOps Blog

MARCH 15, 2023

Data Ingestion : Involves raw data collection from origin and storage using architectures such as batch, streaming or event-driven. Pricing Up to a million events/month on the free plan. Up to 100 million events/month and a 14-day trial for the starter plan. High CPU requirement at data destination for data loading operations.

Data Pipeline 59

Data Pipeline ETL SQL Data Quality 59

AWS Machine Learning Blog

MARCH 30, 2023

Bundesliga and AWS have collaborated to perform an in-depth examination to study the quantification of achievements of Bundesliga’s keepers. How Keeper Efficiency is implemented This Bundesliga Match Fact consumes both event and positional data. This frame is used to synchronize the event data with the positional data.

Machine Learning 102

Machine Learning Machine Learning AWS ML 102

The MLOps Blog

AUGUST 11, 2023

Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., As usage increased, the system had to be scaled vertically, approaching AWS instance-type limits. These include shared-nothing architecture, event-driven architecture, and directed acyclic graphs (DAGs). 1 Data Ingestion (e.g.,

ML 52

ML ML Machine Learning Machine Learning 52