AWS Machine Learning Blog

MARCH 30, 2023

For every xSaves prediction, it produces a message with the prediction as a payload, which then gets distributed by a central message broker running on Amazon Managed Streaming for Apache Kafka (Amazon MSK). The information also gets stored in a data lake for future auditing and model improvements.

Machine Learning 92

Machine Learning Machine Learning AWS ML 92

ODSC - Open Data Science

MAY 24, 2023

Streaming Machine Learning Without a Data Lake The combination of data streaming and ML enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem. Here’s why.

Data Lakes 52

Data Lakes ML ML Analytics 52

AWS Machine Learning Blog

OCTOBER 9, 2024

Configure your Slack workspace You will create one user for each of the following roles: Administrator , Data scientist , Database administrator , Solutions architect and Generic. I am currently using Apache Kafka. See Setting up for Amazon Q Business for more information. Post the first question to Amazon Q Business.

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AWS Apache Kafka Data Scientist Database Administration 127

Dataconomy

FEBRUARY 23, 2023

They are responsible for designing, building, and maintaining the infrastructure and tools needed to manage and process large volumes of data effectively. This involves working closely with data analysts and data scientists to ensure that data is stored, processed, and analyzed efficiently to derive insights that inform decision-making.

Big Data 91

Big Data Big Data Data Engineer Data Engineering 91

Pickl AI

NOVEMBER 4, 2024

They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes. Their work ensures that data flows seamlessly through the organisation, making it easier for Data Scientists and Analysts to access and analyse information.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

AWS Machine Learning Blog

JANUARY 6, 2023

A DataBrew job extracts the data from the TR data warehouse for the users who are eligible to provide recommendations during renewal based on the current subscription plan and recent activity. Then the events are ingested into TR’s centralized streaming platform, which is built on top of Amazon Managed Streaming for Kafka (Amazon MSK).

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AWS Data Warehouse ML ML 86

ODSC - Open Data Science

OCTOBER 9, 2024

Confirmed sessions related to software engineering include: Building Data Contracts with Open-Source Tools Chronon — Open Source Data Platform for AI/ML Creating APIs That Data Scientists Will Love with FastAPI, SQLAlchemy, and Pydantic Using APIs in Data Science Without Breaking Anything Don’t Go Over the Deep End: Building an Effective OSS Management (..)

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Apache Kafka AI AI Machine Learning 40

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. Data scientists and machine learning engineers need to collaborate to make sure that together with the model, they develop robust data pipelines.

Machine Learning 59

Machine Learning Machine Learning ML ML 59

Pickl AI

AUGUST 9, 2024

APIs Understanding how to interact with Application Programming Interfaces (APIs) to gather data from external sources. Data Streaming Learning about real-time data collection methods using tools like Apache Kafka and Amazon Kinesis. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 29, 2024

Limited Support for Real-Time Processing While Hadoop excels at batch processing, it is not inherently designed for real-time data processing. Organisations that require low-latency data analysis may find Hadoop insufficient for their needs.

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Hadoop Clustering Big Data Big Data 52

Mlearning.ai

MAY 16, 2023

The events can be published to a message broker such as Apache Kafka or Google Cloud Pub/Sub. The message broker can then distribute the events to various subscribers such as data processing pipelines, machine learning models, and real-time analytics dashboards.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

phData

SEPTEMBER 27, 2024

Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. Activity Schema Processing : To capture and process customer activities, you might use a stream processing technology like Apache Kafka or Apache Flink.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

The MLOps Blog

AUGUST 11, 2023

Getting a workflow ready which takes your data from its raw form to predictions while maintaining responsiveness and flexibility is the real deal. At that point, the Data Scientists or ML Engineers become curious and start looking for such implementations. 1 Data Ingestion (e.g.,

ML 52

ML ML Machine Learning Machine Learning 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. offers Data Science courses covering essential data tools with a job guarantee. The global Big Data and data engineering market, valued at $75.55

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52