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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KDnuggets

APRIL 1, 2025

This article explains how to create a system that processes data in real time using Apache Kafka and Spark.

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Analytics Vidhya

SEPTEMBER 22, 2022

Dale Carnegie” Apache Kafka is a Software Framework for storing, reading, and analyzing streaming data. The post Build a Simple Realtime Data Pipeline appeared first on Analytics Vidhya. Only knowledge that is used sticks in your mind.- The Internet of Things(IoT) devices can generate a large […].

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Analytics Vidhya

JULY 12, 2023

Best Big Data Softwares - Apache Hadoop, Apache Spark, apache Kafka, Apache Storm, Apache Cassandra, Apache Hive, zoho & more.

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IBM Journey to AI blog

FEBRUARY 12, 2024

At the forefront of this event-driven revolution is Apache Kafka, the widely recognized and dominant open-source technology for event streaming. While most enterprises have already recognized how Apache Kafka provides a strong foundation for EDA, they often fall behind in unlocking its true potential.

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IBM Journey to AI blog

NOVEMBER 3, 2023

Apache Kafka and Apache Flink working together Anyone who is familiar with the stream processing ecosystem is familiar with Apache Kafka: the de-facto enterprise standard for open-source event streaming. With Apache Kafka, you get a raw stream of events from everything that is happening within your business.

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IBM Journey to AI blog

SEPTEMBER 4, 2024

Apache Kafka is an open-source , distributed streaming platform that allows developers to build real-time, event-driven applications. With Apache Kafka, developers can build applications that continuously use streaming data records and deliver real-time experiences to users. How does Apache Kafka work?

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Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. 5 Key Comparisons in Different Apache Kafka Architectures. 5 Key Comparisons in Different Apache Kafka Architectures.

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Analytics Vidhya

JUNE 27, 2020

The post 22 Widely Used Data Science and Machine Learning Tools in 2020 appeared first on Analytics Vidhya. Overview There are a plethora of data science tools out there – which one should you pick up? Here’s a list of over 20.

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Dataconomy

MARCH 11, 2025

Complex Event Processing (CEP) is at the forefront of modern analytics, enabling organizations to extract valuable insights from vast streams of real-time data. Real-time data management The importance of real-time data in todays analytics landscape cannot be overstated.

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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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Dataconomy

JULY 29, 2024

Talks and insights Mikhail Epikhin: Navigating the processor landscape for Apache Kafka Mikhail Epikhin began the session by sharing his team’s research on optimizing Managed Service for Apache Kafka. His presentation focused on the performance and efficiency of different instance types and processor architectures.

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Analytics Vidhya

DECEMBER 4, 2020

appeared first on Analytics Vidhya. Overview Know which are the top 9 skills required to be a data engineer Find suitable resources to learn about these tools By no. The post 9 Must-Have Skills to Become a Data Engineer!

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ODSC - Open Data Science

JUNE 1, 2023

Be sure to check out his talk, “ Building a Real-time Analytics Application for a Pizza Delivery Service ,” there! Gartner defines Real-Time Analytics as follows: Real-time analytics is the discipline that applies logic and mathematics to data to provide insights for making better decisions quickly.

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phData

MAY 3, 2024

Leveraging real-time analytics to make informed decisions is the golden standard for virtually every business that collects data. If you have the Snowflake Data Cloud (or are considering migrating to Snowflake ), you’re a blog away from taking a step closer to real-time analytics. Why Pursue Real-Time Analytics for Your Organization?

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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. IBM provides an Event Streams capability build on Apache Kafka that makes events manageable across an entire enterprise.

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Data Science Blog

JUNE 27, 2023

Big Data Analytics stands apart from conventional data processing in its fundamental nature. It receives batch views from the batch layer and near-real-time views from the speed layer, utilizing this data to facilitate standard reporting and ad hoc analytics.

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Precisely

DECEMBER 28, 2023

More than ever, advanced analytics, ML, and AI are providing the foundation for innovation, efficiency, and profitability. It also allows for applications, analytics, and reporting to process information as it happens. One very popular platform is Apache Kafka , a powerful open-source tool used by thousands of companies.

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Data Science Dojo

JULY 24, 2023

Apache Flink for stream processing: Wrapping up In conclusion, stream processing with distributed systems like Apache Kafka, Apache Flink, and Apache Spark Streaming empowers organizations to harness real-time data insights, enabling timely decision-making and enhanced user experiences.

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IBM Journey to AI blog

AUGUST 29, 2024

Apache Flink takes raw events and processes them, making them more relevant in the broader business context. The unique advantages of Apache Flink Apache Flink augments event streaming technologies like Apache Kafka to enable businesses to respond to events more effectively in real time.

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ODSC - Open Data Science

MAY 24, 2023

Building a Business with a Real-Time Analytics Stack, Streaming ML Without a Data Lake, and Google’s PaLM 2 Building a Pizza Delivery Service with a Real-Time Analytics Stack The best businesses react quickly and with informed decisions. Here’s a use case of how you can use a real-time analytics stack to build a pizza delivery service.

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Women in Big Data

OCTOBER 9, 2024

After this, the data is analyzed, business logic is applied, and it is processed for further analytical tasks like visualization or machine learning. Data Ingestion: Data is collected and funneled into the pipeline using batch or real-time methods, leveraging tools like Apache Kafka, AWS Kinesis, or custom ETL scripts.

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insideBIGDATA

JUNE 25, 2024

In this contributed article, Sijie Guo, Founder and CEO of Streamnative, believes that with remote work entrenched in the post-pandemic enterprise, organizations are restructuring their technology stack and software strategy for a new, distributed workforce.

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Dataversity

JUNE 30, 2023

The demand for instant results is not limited […] The post Architecting Real-Time Analytics for Speed and Scale appeared first on DATAVERSITY. If Netflix takes too long to load or the nearest Lyft is too far, users are quick to switch to alternative options.

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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.

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IBM Journey to AI blog

NOVEMBER 29, 2023

Stream analytics can be used to help improve the speed and accuracy of models’ predictions. IBM Event Automation is a fully composable solution, built on open technologies, with capabilities for: Event streaming : Collect and distribute raw streams of real-time business events with enterprise-grade Apache Kafka.

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AWS Machine Learning Blog

MARCH 10, 2023

The same architecture applies if you use Amazon Managed Streaming for Apache Kafka (Amazon MSK) as a data streaming service. You can use this metadata in your data analytics solutions, machine learning model training tasks, or visualizations and dashboards that consume transaction data. An example use case is claims processing.

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insideBIGDATA

JUNE 25, 2024

In this contributed article, Sijie Guo, Founder and CEO of Streamnative, believes that with remote work entrenched in the post-pandemic enterprise, organizations are restructuring their technology stack and software strategy for a new, distributed workforce.

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ODSC - Open Data Science

FEBRUARY 6, 2024

Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer. REGISTER NOW Data Orchestration and Workflow Management Apache Airflow Apache Airflow is renowned for its ability to build and schedule complex data pipelines.

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Pickl AI

JULY 20, 2023

Top 15 Data Analytics Projects in 2023 for Beginners to Experienced Levels: Data Analytics Projects allow aspirants in the field to display their proficiency to employers and acquire job roles. However, you might be looking for a guide to help you understand the different types of Data Analytics projects you may undertake.

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Pickl AI

SEPTEMBER 18, 2024

As a pioneer in the streaming industry, Netflix utilises advanced data analytics to enhance user experience, optimise operations, and drive strategic decisions. 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.

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Flipboard

NOVEMBER 21, 2023

For this particular use case, you can use streaming ingestion with Amazon SageMaker Feature Store and Amazon Managed Streaming for Apache Kafka, MSK, to make machine learning-backed decisions in near real-time. He is also pursuing an MBA in Machine Learning and Business Analytics from Babson College, Boston.

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Precisely

JULY 21, 2023

Used by more than 75% of the Fortune 500, Apache Kafka has emerged as a powerful open source data streaming platform to meet these challenges. But harnessing and integrating Kafka’s full potential into enterprise environments can be complex. This is where Confluent steps in.

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Pickl AI

JULY 25, 2024

This is essential for applications that demand immediate insights, such as fraud detection or real-time analytics. By centralising data from disparate sources, organisations can ensure that they have a unified view of their information, which is vital for analytics, reporting, and decision-making.

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AWS Machine Learning Blog

OCTOBER 9, 2024

Anomaly detection can be done on your analytics data through Redshift ML by using the included XGBoost model type, local models, or remote models with Amazon SageMaker. To learn more about the beta offering, see Anomaly detection in streaming time series data with online learning using Amazon Managed Service for Apache Flink.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

Common examples of time series data include sales revenue, system performance data (such as CPU utilization and memory usage), credit card transactions, sensor readings, and user activity analytics. Time series anomaly detection is the process of identifying unexpected or unusual patterns in data that unfold over time.

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Precisely

SEPTEMBER 12, 2023

Precisely data integrity solutions fuel your Confluent and Apache Kafka streaming data pipelines with trusted data that has maximum accuracy, consistency, and context and we’re ready to share more with you at the upcoming Current 2023. Let’s cover some additional information to know before attending.

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