Towards Data Science

FEBRUARY 18, 2024

How to Stream and Apply Real-Time Prediction Models on High-Throughput Time-Series Data Photo by JJ Ying on Unsplash Most of the stream processing libraries are not python friendly while the majority of machine learning and data mining libraries are python based. This design enables the re-reading of old messages.

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Kafka Python Process Google Cloud 98

Confluent

OCTOBER 10, 2019

A key challenge, however, is integrating devices and machines to process the data in real time and at scale. Apache Kafka ® and its surrounding ecosystem, which includes Kafka Connect, Kafka Streams, and KSQL, have become the technology of choice for integrating and processing these kinds of datasets.

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Kafka Google Cloud Architecture Machine Learning 20

Towards Data Science

FEBRUARY 9, 2024

Ideal for those new to data systems or language model applications, this project is structured into two segments: This initial article guides you through constructing a data pipeline utilizing Kafka for streaming, Airflow for orchestration, Spark for data transformation, and PostgreSQL for storage. Image by the author.

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Kafka Data Engineering Data Engineer PostgreSQL 98

Pinterest Engineering

NOVEMBER 18, 2024

CDC allows applications to respond to these changes in real-time, making it an essential component for data integration, replication, and synchronization. Real-Time Data Processing : CDC enables real-time data processing by capturing changes as they happen. Why is CDC Important?

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Kafka MySQL Database Software Engineer 49

LinkedIn Engineering

JANUARY 19, 2024

Data consistency, feature reliability, processing scalability, and end-to-end observability are key drivers to ensuring business as usual (zero disruptions) and a cohesive customer experience. With our new data processing framework, we were able to observe a multitude of benefits, including 99.9%

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AltexSoft

OCTOBER 21, 2022

Kafka can continue the list of brand names that became generic terms for the entire type of technology. Similar to Google in web browsing and Photoshop in image processing, it became a gold standard in data streaming, preferred by 70 percent of Fortune 500 companies. What is Kafka? What Kafka is used for.

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Cloudera

SEPTEMBER 26, 2023

Organizations increasingly rely on streaming data sources not only to bring data into the enterprise but also to perform streaming analytics that accelerate the process of being able to get value from the data early in its lifecycle.

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Kafka Technology IT Government 95

Data Engineering Podcast

DECEMBER 31, 2018

What are the use cases for Pravega and how does it fit into the data ecosystem? How does it compare with systems such as Kafka and Pulsar for ingesting and persisting unbounded data? One of the compelling aspects of Pravega is the automatic sharding and resource allocation for variations in data patterns.

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Netflix Tech

FEBRUARY 14, 2025

After raw events are collected into a centralized queue, a custom event extractor processes this data to identify and extract all impression events. This refined output is then structured using an Avro schema, establishing a definitive source of truth for Netflixs impression data.

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Workfall

JUNE 27, 2023

It means that there is a high risk of data loss but Apache Kafka solves this because it is distributed and can easily scale horizontally and other servers can take over the workload seamlessly. It offers a unified solution to real-time data needs any organisation might have. This is where Apache Kafka comes in.

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Kafka Architecture AWS Transportation 75

Striim

MARCH 21, 2025

To access real-time data, organizations are turning to stream processing. There are two main data processing paradigms: batch processing and stream processing. Your electric consumption is collected during a month and then processed and billed at the end of that period.

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Data Engineering Weekly

MAY 16, 2023

Architectural Patterns for Data Quality Now we understand the trade-off between speed & correctness and the difference between data testing and observability. Let’s talk about the data processing types. Two-Phase WAP The Two-Phase WAP, as the name suggests, follows two copy processes.

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Cloudera

AUGUST 2, 2021

Setting the context, why would a customer want to use Apache NiFi, Apache Kafka, and Apache HBase? Because, they’ll be able to store massive amounts of data, process this data in real-time or batch, and serve the data to other applications.

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Team Data Science

MAY 10, 2020

Kafka, while not in the top 5 most in demand skills, was still the most requested buffer technology requested which makes it worthwhile to include it. I'll use Python and Spark because they are the top 2 requested skills in Toronto.

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Knowledge Hut

JANUARY 18, 2024

“Big data Analytics” is a phrase that was coined to refer to amounts of datasets that are so large traditional data processing software simply can’t manage them. For example, big data is used to pick out trends in economics, and those trends and patterns are used to predict what will happen in the future.

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Data Process Process Hadoop Scala 52

LinkedIn Engineering

OCTOBER 19, 2023

Authors: Bingfeng Xia and Xinyu Liu Background At LinkedIn, Apache Beam plays a pivotal role in stream processing infrastructures that process over 4 trillion events daily through more than 3,000 pipelines across multiple production data centers.

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Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. For now, we’ll focus on Kafka.

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ProjectPro

FEBRUARY 8, 2023

Did you know thousands of businesses, including over 80% of the Fortune 100, use Apache Kafka to modernize their data strategies? Apache Kafka is the most widely used open-source stream-processing solution for gathering, processing, storing, and analyzing large amounts of data. What is Apache Kafka Used For?

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Monte Carlo

NOVEMBER 21, 2024

Think of it as the “slow and steady wins the race” approach to data processing. Stream Processing Pattern Now, imagine if instead of waiting to do laundry once a week, you had a magical washing machine that could clean each piece of clothing the moment it got dirty.

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Confluent

JUNE 18, 2019

Distributed transactions are very hard to implement successfully, which is why we’ll introduce a log-inspired system such as Apache Kafka ®. Building an indexing pipeline at scale with Kafka Connect. Moving data into Apache Kafka with the JDBC connector. Setting up the connector.

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Afterpay Tech

SEPTEMBER 6, 2022

Photo by Leon S on Unsplash By: Jing Li Summary This article articulates the challenges, innovation and success of the Kafka implementation in Afterpay’s Global Payments Platform in the PCI zone. Context The asynchronous processing capability that Kafka offers opens up numerous innovation opportunities to interact with other services.

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Confluent

JUNE 12, 2019

Confluent Cloud, a fully managed event cloud-native streaming service that extends the value of Apache Kafka ® , is simple, resilient, secure, and performant, allowing you to focus on what is important—building contextual event-driven applications, not infrastructure. KSQL and Kafka Connect example. and Helm/Tiller 2.8.2+

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Cloud Kafka Healthcare Software Engineering 94

Netflix Tech

AUGUST 1, 2022

Overall Architecture The Data Mesh system can be divided into the control plane (Data Mesh Controller) and the data plane (Data Mesh Pipeline). Once deployed, the pipeline performs the actual heavy lifting data processing work. Connectors A source connector is a Data Mesh managed producer.

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Process Transportation Kafka Entertainment 109

Christophe Blefari

DECEMBER 16, 2022

Query your data in Kafka using SQL — This is a post that compares Flink, ksqlDB, Trino, Materialize, RisingWave and timeplus (the authors) in order to query Kafka. Even if it's vendor oriented this is a good starting point to have an overview of what you can expect from these tools.

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ProjectPro

JANUARY 25, 2022

Features of PySpark Features that contribute to PySpark's immense popularity in the industry- Real-Time Computations PySpark emphasizes in-memory processing, which allows it to perform real-time computations on huge volumes of data. PySpark is used to process real-time data with Kafka and Streaming, and this exhibits low latency.

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Confluent

SEPTEMBER 25, 2019

Apache Kafka ® and its uses. The founders of Confluent originally created the open source project Apache Kafka while working at LinkedIn, and over recent years Kafka has become a foundational technology in the movement to event streaming. In retail, companies like Walmart , Target , and Nordstrom have adopted Kafka.

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Database-centric Kafka Pipeline-centric Retail 56

Striim

AUGUST 5, 2024

This episode promises invaluable insights into the shift from batch to real-time data processing, and the practical applications across multiple industries that make this transition not just beneficial but necessary. Explore the intricate challenges and groundbreaking innovations in data storage and streaming.

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Kafka Data Storage Architecture Data Architecture 52

AltexSoft

JULY 18, 2023

This module can ingest live data streams from multiple sources, including Apache Kafka , Apache Flume , Amazon Kinesis , or Twitter, splitting them into discrete micro-batches. Netflix leverages Spark Streaming and Kafka for near real-time movie recommendations. Big data processing.

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Christophe Blefari

JANUARY 14, 2023

On the data processing side there is Polars, a DataFrame library that could replace pandas. How to land a job in progressive data — If you want to use your skills to Do Good you have to look at Brittany's post about progressive data. Let's have a quick look at it. I did not read it yet but it looks great.

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Cloudera

JANUARY 20, 2021

Balancing the edge: Understanding the right balance between data processing at the edge and in the cloud is a challenge, and this is why the entire data lifecycle needs to be considered. To keep the example simple, the following data attribute tags were chosen for each part generated by the factories: .

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Cloudera

OCTOBER 7, 2021

A data mesh can be defined as a collection of “nodes”, typically referred to as Data Products, each of which can be uniquely identified using four key descriptive properties: . The Value Proposition of CDF in Data Mesh Implementations.

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Data Engineering Weekly

FEBRUARY 2, 2025

I finally found a good critique that discusses its flaws, such as multi-hop architecture, inefficiencies, high costs, and difficulties maintaining data quality and reusability. The article advocates for a "shift left" approach to data processing, improving data accessibility, quality, and efficiency for operational and analytical use cases.

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Data Engineering Data Engineer Engineering Data Lake 57

Data Engineering Podcast

APRIL 1, 2018

How much configuration do you provide to the end user in terms of the captured data, such as sampling rate or additional context? I understand that your original architecture used RabbitMQ as your ingest mechanism, which you then migrated to Kafka. For someone who wants to start using ThreatStack, what does the setup process look like?

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Pinterest Engineering

NOVEMBER 28, 2023

Pinterest’s real-time metrics asynchronous data processing pipeline, powering Pinterest’s time series database Goku, stood at the crossroads of opportunity. The mission was clear: identify bottlenecks, innovate relentlessly, and propel our real-time analytics processing capabilities into an era of unparalleled efficiency.

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Kafka Bytes Architecture Software Engineer 104

Cloudera

MARCH 2, 2023

Recently, we announced enhanced multi-function analytics support in Cloudera Data Platform (CDP) with Apache Iceberg. Iceberg is a high-performance open table format for huge analytic data sets. The post Streaming Ingestion for Apache Iceberg With Cloudera Stream Processing appeared first on Cloudera Blog.

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Process SQL Kafka Database 114

Cloudera

JULY 18, 2022

The streaming analytics process that we will implement in this blog aims to identify potentially fraudulent transactions by checking for transactions that happen at distant geographical locations within a short period of time. Flink is a “streaming first” modern distributed system for data processing. Registering catalogs.

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Process Kafka Scala SQL 91

Cloudera

NOVEMBER 2, 2020

An AdTech company in the US provides processing, payment, and analytics services for digital advertisers. Data processing and analytics drive their entire business. But an important caveat is that ingest speed, semantic richness for developers, data freshness, and query latency are paramount. Data Hub – .

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