Apache Kafka, Big Data Analytics and Database

Apache Kafka use cases: Driving innovation across diverse industries

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?

Apache Kafka

Apache Kafka Internet of Things Data Pipeline Clustering

Big Data – Lambda or Kappa Architecture?

Data Science Blog

JUNE 27, 2023

Big Data Analytics stands apart from conventional data processing in its fundamental nature. In the realm of Big Data, there are two prominent architectural concepts that perplex companies embarking on the construction or restructuring of their Big Data platform: Lambda architecture or Kappa architecture.

Big Data

Big Data Big Data Apache Kafka Database

How Netflix Applies Big Data Across Business Verticals: Insights and Strategies

Pickl AI

SEPTEMBER 18, 2024

Data at Rest This includes storage solutions such as S3 Data Warehouse and Cassandra. These systems handle the storage costs associated with keeping vast amounts of content and user data. The platform employs Big Data analytics to monitor user interactions in real time.

Big Data

Big Data Big Data Apache Kafka Big Data Analytics

Webinars

How to Achieve High-Accuracy Results When Using LLMs

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Big Data Syllabus: A Comprehensive Overview

Pickl AI

AUGUST 9, 2024

Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities. Businesses need to analyse data as it streams in to make timely decisions. This diversity requires flexible data processing and storage solutions.

Big Data

Big Data Big Data Big Data Analytics Big Data Analytics

A Comprehensive Guide to the main components of Big Data

Pickl AI

DECEMBER 2, 2024

This massive influx of data necessitates robust storage solutions and processing capabilities. Variety Variety indicates the different types of data being generated. This includes structured data (like databases), semi-structured data (like XML files), and unstructured data (like text documents and videos).

Big Data

Big Data Big Data Data Lakes Apache Hadoop

A Comprehensive Guide to the Main Components of Big Data

Pickl AI

NOVEMBER 25, 2024

This massive influx of data necessitates robust storage solutions and processing capabilities. Variety Variety indicates the different types of data being generated. This includes structured data (like databases), semi-structured data (like XML files), and unstructured data (like text documents and videos).

Big Data

Big Data Big Data Data Lakes Apache Hadoop

What is a Hadoop Cluster?

Pickl AI

JULY 29, 2024

It utilises the Hadoop Distributed File System (HDFS) and MapReduce for efficient data management, enabling organisations to perform big data analytics and gain valuable insights from their data. Organisations that require low-latency data analysis may find Hadoop insufficient for their needs.

Hadoop

Hadoop Clustering Big Data Big Data

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

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.

ML

ML ML Apache Kafka SQL

ML Pipeline Architecture Design Patterns (With 10 Real-World Examples)

The MLOps Blog

AUGUST 11, 2023

1 Data Ingestion (e.g., Apache Kafka, Amazon Kinesis) 2 Data Preprocessing (e.g., Today different stages exist within ML pipelines built to meet technical, industrial, and business requirements. This section delves into the common stages in most ML pipelines, regardless of industry or business function.

ML

ML ML Machine Learning Machine Learning

Predicting the Future of Data Science

Pickl AI

DECEMBER 4, 2024

This explosive growth is driven by the increasing volume of data generated daily, with estimates suggesting that by 2025, there will be around 181 zettabytes of data created globally. Real-Time Data Processing The demand for real-time analytics is growing as businesses seek immediate insights to drive decision-making.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

Top Big Data Tools Every Data Professional Should Know

Pickl AI

FEBRUARY 23, 2025

Summary: Big Data tools empower organizations to analyze vast datasets, leading to improved decision-making and operational efficiency. Ultimately, leveraging Big Data analytics provides a competitive advantage and drives innovation across various industries.

Big Data

Big Data Big Data Apache Hadoop Apache Kafka

Data Science Current

Apache Kafka use cases: Driving innovation across diverse industries

Big Data – Lambda or Kappa Architecture?

Webinars

Trending Sources

How Netflix Applies Big Data Across Business Verticals: Insights and Strategies

Webinars

Big Data Syllabus: A Comprehensive Overview

Top Big Data Interview Questions for 2025

A Comprehensive Guide to the main components of Big Data

A Comprehensive Guide to the Main Components of Big Data

What is a Hadoop Cluster?

Use streaming ingestion with Amazon SageMaker Feature Store and Amazon MSK to make ML-backed decisions in near-real time

ML Pipeline Architecture Design Patterns (With 10 Real-World Examples)

Predicting the Future of Data Science

Top Big Data Tools Every Data Professional Should Know

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