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.

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Big Data Big Data Apache Kafka Database 130

AWS Machine Learning Blog

OCTOBER 9, 2024

Using Amazon CloudWatch for anomaly detection Amazon CloudWatch supports creating anomaly detectors on specific Amazon CloudWatch Log Groups by applying statistical and ML algorithms to CloudWatch metrics. To use this feature, you can write rules or analyzers and then turn on anomaly detection in AWS Glue ETL.

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ODSC - Open Data Science

OCTOBER 9, 2024

Tools like Harness and JenkinsX use machine learning algorithms to predict potential deployment failures, manage resource usage, and automate rollback procedures when something goes wrong. In the world of DevOps, AI can help monitor infrastructure, analyze logs, and detect performance bottlenecks in real-time.

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Apache Kafka AI AI Machine Learning 40

Pickl AI

AUGUST 9, 2024

Data Integration Tools Technologies such as Apache NiFi and Talend help in the seamless integration of data from various sources into a unified system for analysis. Understanding ETL (Extract, Transform, Load) processes is vital for students. Finance Applications in fraud detection, risk assessment, and algorithmic trading.

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Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 8, 2024

Tools such as Python’s Pandas library, Apache Spark, or specialised data cleaning software streamline these processes, ensuring data integrity before further transformation. This step often involves: ETL Processes: Extracting, transforming, and loading data into a target system.

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Data Pipeline Data Quality Database Apache Kafka 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.

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Data Pipeline ETL SQL Data Quality 59

DagsHub

APRIL 7, 2024

Image generated with Midjourney In today’s fast-paced world of data science, building impactful machine learning models relies on much more than selecting the best algorithm for the job. Flexibility: Its use cases are wider than just machine learning; for example, we can use it to set up ETL pipelines.

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Machine Learning Machine Learning ML ML 59