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. They are able to combine event topics to identify patterns or aggregates to analyze trends and detect anomalies. This approach then enables them to build new responsive applications.

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The MLOps Blog

FEBRUARY 5, 2023

There are a number of tools that can help with streaming data collection and processing, some popular ones include: Apache Kafka : An open-source, distributed event streaming platform that can handle millions of events per second. For setting up streaming/continuous flow of data, we will be using Kafka and Zookeeper. kafka_2.13 -3.3.2.tgz

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phData

MARCH 7, 2023

While building a whole new application might sound like a lot of work, if you’re already using Kafka to connect to Snowflake, you can upgrade your connection to version 1.8 and have your Kafka connector use the Streaming Ingest SDK instead of writing messages or streams to an internal stage.

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Towards AI

FEBRUARY 12, 2024

It was a simple structured streaming pipeline that was listening to a Kafka topic for events and performing some transformations on it, before emitting the output to another Kafka topic. I was recently caught in such a debugging train when one of my pipelines was taking longer than expected.

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ODSC - Open Data Science

JUNE 1, 2023

We’re going to assume that the pizza service already captures orders in Apache Kafka and is also keeping a record of its customers and the products that they sell in MySQL. We can solve this problem using just the data in the orders topic. The config to connect to Kafka is defined under tableIndexConfig.streamConfigs.

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ODSC - Open Data Science

APRIL 20, 2023

Streamlining Your Streaming Analytics with Delta Lake & Rust Gary Nakanelua | Managing Director, Innovation | Blueprint Technologies (BPCS) Join this session to learn how to get started with a streaming architecture using Delta Lake and Kafka on Azure. Topics covered will range from ML-based recommendations to user-friendly interfaces.

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Mlearning.ai

JULY 21, 2023

I have been writing about Apache Spark recently and published articles on this topic. In this example, we will assume data is coming through a socket connection but in real world examples Kafka would be a better choice. In a real-world scenario, data could potentially be streaming from various sources, like Kafka.

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ODSC - Open Data Science

JULY 22, 2023

The week was filled with engaging sessions on top topics in data science, innovation in AI, and smiling faces that we haven’t seen in a while. We had bigger sessions on getting started with machine learning or SQL, up to advanced topics in NLP, and how to make deepfakes.

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ODSC - Open Data Science

MARCH 6, 2023

In an effort to learn more about our community, we recently shared a survey about machine learning topics, including what platforms you’re using, in what industries, and what problems you’re facing. A good amount of people intend to use Hugging Face Transformers, Kafka, MLFlow, PyTorch, and TensorFlow.

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ODSC - Open Data Science

JUNE 29, 2023

8 Trending and New Large Language Models to Keep an Eye On Large language models are the dominant topics in conversations about AI now, and here are eight newer and trending ones to pay attention to. Learn more about how you can speak and present at ODSC West here!

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AWS Machine Learning Blog

NOVEMBER 3, 2023

m How it’s implemented In our quest to accurately determine shot speed during live matches, we’ve implemented a cutting-edge solution using Amazon Managed Streaming for Apache Kafka (Amazon MSK). These Lambda functions and Fargate containers then make this data available for further use in the appropriate MSK topics.

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AWS Machine Learning Blog

MARCH 30, 2023

To ensure real-time updates of ball recovery times, we have implemented Amazon Managed Streaming for Apache Kafka (Amazon MSK) as a central solution for data streaming and messaging. Both the Lambda function and the Fargate container publish the data for further consumption in the relevant MSK topics.

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phData

APRIL 18, 2024

We will ingest data using Confluent Kafka and enable Schema detection in the Kafka connector. In the current process, Snowflake supports detection and evolution for CSV, Parquet, and JSON in files and JSON within streaming data from Kafka. This is very helpful during batch loading using the COPY command or while using Snowpipe.

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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.

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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.

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phData

MARCH 1, 2024

In our role as Solution Architects , we engage in various discussions with clients regarding data ingestion, transformation, and related topics. In the next blog, we will see how to use Schema evolution with Kafka to automate the creation of fields as the data is ingested. For the older records, the value will be set to NULL.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Analytics Vidhya

FEBRUARY 28, 2024

We know that streaming data is data that is emitted at high volume […] The post Kafka to MongoDB: Building a Streamlined Data Pipeline appeared first on Analytics Vidhya. IT industries rely heavily on real-time insights derived from streaming data sources.

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ODSC - Open Data Science

MAY 31, 2023

Be sure to check out his talk, “ Apache Kafka for Real-Time Machine Learning Without a Data Lake ,” there! The combination of data streaming and machine learning (ML) enables you to build one scalable, reliable, but also simple infrastructure for all machine learning tasks using the Apache Kafka ecosystem.

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Analytics Vidhya

MARCH 10, 2023

Introduction Apache Kafka is a framework for dealing with many real-time data streams in a way that is spread out. It was made on LinkedIn and shared with the public in 2011.

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ODSC - Open Data Science

FEBRUARY 2, 2023

Data Science Skills and Competencies Aside from knowing particular frameworks and languages, there are various topics and competencies that any data scientist should know. Kafka is the only notable streaming platform to make any lists, but it’s the gold standard for real-time analytics and streaming so that makes sense.

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O'Reilly Media

SEPTEMBER 15, 2021

What about Kafka? Kafka, Spark, Google BigQuery, and Dask were in the middle, with a lot of users (15%, 19%, 8%, and 5%) and above-average salaries ($179,000, $172,000, $170,000, and $170,000). It wasn’t a surprise that most of the respondents said machine learning (63%)—these days, ML is the hottest topic in the data world.

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Analytics Vidhya

NOVEMBER 2, 2020

Overview Learn about viewing data as streams of immutable events in contrast to mutable containers Understand how Apache Kafka captures real-time data through event. The post Apache Kafka: A Metaphorical Introduction to Event Streaming for Data Scientists and Data Engineers appeared first on Analytics Vidhya.

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Pickl AI

JULY 20, 2023

NLP techniques help extract insights, sentiment analysis, and topic modeling from text data. Real-time Data Stream Analysis: Use Python with libraries like Apache Kafka and Apache Spark to process and analyze real-time data streams from sources like Twitter, sensors, or website logs.

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Snorkel AI

JUNE 27, 2023

And that’s the topic that we will talk about today. So I’ll cover three topics: first, online predictions, and then continual learning, and then real-time monitoring, which is extremely important to enable continual learning. This brings us to the next topic, monitoring. And here’s my email. Here’s my Twitter.

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Snorkel AI

JUNE 27, 2023

And that’s the topic that we will talk about today. So I’ll cover three topics: first, online predictions, and then continual learning, and then real-time monitoring, which is extremely important to enable continual learning. This brings us to the next topic, monitoring. And here’s my email. Here’s my Twitter.

AI 52

AI AI Data Warehouse Machine Learning 52

IBM Journey to AI blog

JUNE 26, 2023

Scenario 3: Break the operational bottleneck caused by Kafka, an open-source data extraction tool. Finally, there was no Kafka technical support or after-sales guarantee, resulting in the need for ongoing investment in staff training and expert consulting services.

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The Data Administration Newsletter

FEBRUARY 15, 2022

Most large technology businesses collect data from their consumers in a variety of methods, and the majority of the time, this data is in its raw form. However, when data is presented in an understandable and accessible style, it may assist and drive business requirements. The task is to process the data and, if required, […].

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phData

APRIL 18, 2023

Snowflake’s Kafka Connector automatically ingests data directly from a Kafka topic in real-time, Snowpipe is an entirely serverless process, and Snowflake manages the operation entirely, scaling out the compute as needed.

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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. Nov-01,22:05:05 4 200.00

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Mlearning.ai

MAY 16, 2023

The events can be published to a message broker such as Apache Kafka or Google Cloud Pub/Sub. The serving layer would then present the combined data in a dashboard or report, including information on how many people are talking about a particular topic, how they are talking about it, and where they are located.

Data Engineering 52

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Precisely

JUNE 12, 2023

This raises the topic of data integrity, which is a business imperative. Precisely Connect simplifies integration between mainframe systems and popular modern platforms such as Snowflake , Confluent , and Kafka. Rather, it is to integrate mission-critical systems in a way that serves the needs of the business.

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phData

SEPTEMBER 20, 2023

Use Cases for Data Mesh in Snowflake Data mesh has become a very popular topic in the data engineering world as of late, but it’s not for everyone. This intermediate layer could be Kafka topics that feed into Snowflake via continuous ingestion followed by automatic updates of data products in Snowflake.

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The MLOps Blog

JULY 18, 2023

Every episode is focused on one specific ML topic, and during this one, we talked to Jason Falks about deploying conversational AI products to production. And on the topic of equipment, you were involved in developing the Connect, right? (Or Kafka : our pipelining solution for passing messages between all the systems.

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AWS Machine Learning Blog

JANUARY 20, 2023

A Lambda function called notifications is subscribed to this SNS topic. If the prediction is the final output of the step function and the callback mode is “Webhook” [or email, message brokers (Kafka), etc.], By Process Input or GetTransformCall Lambda when a synchronous SageMaker endpoint has returned a prediction.

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phData

DECEMBER 4, 2023

More on this topic later; but for now, keep in mind that the simplest method is to create a naming convention for database objects that allows you to identify the owner and associated budget. You will find options for most major data migration tools and technologies like Kafka and Spark. Load it as-is and see how queries perform.

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