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 58

Apache Kafka Internet of Things Data Pipeline Clustering 58

Pickl AI

DECEMBER 2, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

Pickl AI

NOVEMBER 25, 2024

Key Takeaways Big Data originates from diverse sources, including IoT and social media. Data lakes and cloud storage provide scalable solutions for large datasets. Processing frameworks like Hadoop enable efficient data analysis across clusters.

Big Data 52

Big Data Big Data Data Lakes Apache Hadoop 52

The MLOps Blog

FEBRUARY 5, 2023

We will also get familiar with tools that can help record this data and further analyse it. In the later part of this article, we will discuss its importance and how we can use machine learning for streaming data analysis with the help of a hands-on example. What is streaming data?

Machine Learning 72

Machine Learning Machine Learning Data Pipeline Apache Kafka 72

Pickl AI

JULY 29, 2024

Internet of Things (IoT) Hadoop clusters can handle the massive amounts of data generated by IoT devices, enabling real-time processing and analysis of sensor data. Limited Support for Real-Time Processing While Hadoop excels at batch processing, it is not inherently designed for real-time data processing.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

Pickl AI

JULY 20, 2023

Web and App Analytics Projects: These projects involve analyzing website and app data to understand user behaviour, improve user experience, and optimize conversion rates. Kaggle datasets) and use Python’s Pandas library to perform data cleaning, data wrangling, and exploratory data analysis (EDA).

Analytics 40

Analytics Analytics Big Data Big Data 40