Analytics, Apache Kafka and Azure - Data Science Current

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

Streaming Machine Learning Without a Data Lake

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.

Data Lakes

Data Lakes Machine Learning Machine Learning Apache Kafka

Top Big Data Tools Every Data Professional Should Know

Pickl AI

FEBRUARY 23, 2025

Ultimately, leveraging Big Data analytics provides a competitive advantage and drives innovation across various industries. Competitive Advantage Organisations that leverage Big Data Analytics can stay ahead of the competition by anticipating market trends and consumer preferences.

Big Data

Big Data Big Data Apache Hadoop Apache Kafka

What Are AI Credits and How Can Data Scientists Use Them?

ODSC - Open Data Science

APRIL 23, 2025

Confluent Confluent provides a robust data streaming platform built around Apache Kafka. Microsoft Azure Azure supports AI development through tools like Azure ML Studio, virtual machines, and Azure OpenAI integration. Explore Real-Time and Streaming Data UseCases Tools like Confluent and Vespa.ai

Data Scientist

Data Scientist Azure Apache Kafka ML

Best Data Engineering Tools Every Engineer Should Know

Pickl AI

MARCH 19, 2025

Python, SQL, and Apache Spark are essential for data engineering workflows. Real-time data processing with Apache Kafka enables faster decision-making. Apache Spark Apache Spark is a powerful data processing framework that efficiently handles Big Data. The global Big Data and data engineering market, valued at $75.55

Data Engineering

Data Engineering Data Engineering Data Engineer Data Engineering

11 Open-Source Data Engineering Tools Every Pro Should Use

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.

Data Engineering

Data Engineering Data Engineer Data Engineering Data Engineering

Predicting the Future of Data Science

Pickl AI

DECEMBER 4, 2024

Summary: The future of Data Science is shaped by emerging trends such as advanced AI and Machine Learning, augmented analytics, and automated processes. Data privacy regulations will shape how organisations handle sensitive information in analytics. Continuous learning and adaptation will be essential for data professionals.

Data Science

Data Science Data Scientist Machine Learning Machine Learning

What is Data Ingestion? Understanding the Basics

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.

Apache Kafka

Apache Kafka Data Lakes Data Warehouse Data Quality

Discover the Most Important Fundamentals of Data Engineering

Pickl AI

NOVEMBER 4, 2024

It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. OLAP (Online Analytical Processing): OLAP tools allow users to analyse data from multiple perspectives. ETL is vital for ensuring data quality and integrity.

Data Engineering

Data Engineering Data Engineer Data Engineering Data Engineering

A Comprehensive Guide to the main components of Big Data

Pickl AI

DECEMBER 2, 2024

Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Analytics tools help convert raw data into actionable insights for businesses. Real-time analytics are becoming increasingly important for businesses that need to respond quickly to market changes. What is Big Data?

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

Key components include data storage solutions, processing frameworks, analytics tools, and governance practices. Analytics tools help convert raw data into actionable insights for businesses. Real-time analytics are becoming increasingly important for businesses that need to respond quickly to market changes. What is Big Data?

Big Data

Big Data Big Data Data Lakes Apache Hadoop

Training Models on Streaming Data [Practical Guide]

The MLOps Blog

FEBRUARY 5, 2023

With that capability, applications, analytics, and reporting can be done in real-time. 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.

Machine Learning

Machine Learning Machine Learning Data Pipeline Apache Kafka

A Simple Guide to Real-Time Data Ingestion

Pickl AI

JULY 24, 2023

Social Media Analytics: Companies may want to analyze real-time social media data to track trends, customer sentiment, and brand mentions as they happen. Streaming Analytics: Many businesses use real-time data ingestion to analyze streaming data from various sources, such as clickstreams, log files, and application metrics.

Internet of Things

Internet of Things Apache Kafka ETL Azure

How to Manage Unstructured Data in AI and Machine Learning Projects

DagsHub

OCTOBER 23, 2024

A central repository for unstructured data is beneficial for tasks like analytics and data virtualization. Tools and Techniques to Manage Unstructured Data Several tools are required to properly manage unstructured data, from storage to analytical tools. Popular data lake solutions include Amazon S3 , Azure Data Lake , and Hadoop.

Machine Learning

Machine Learning Machine Learning Data Lakes AI

The Evolution of Customer Data Modeling: From Static Profiles to Dynamic Customer 360

phData

SEPTEMBER 27, 2024

Technologies like Apache Kafka, often used in modern CDPs, use log-based approaches to stream customer events between systems in real-time. It enables advanced analytics, makes debugging your marketing automations easier, provides natural audit trails for compliance, and allows for flexible, evolving customer data models.

Data Modeling

Data Modeling Data Models Apache Kafka Data Lakes

How to Build a Real-Time Data Analytics Platform with Snowflake and AWS

phData

MAY 15, 2025

This incredible capability is known as Real-Time Data Analytics , and it is revolutionizing the way we understand and utilize information. In this blog, we will uncover: What is real-time analytics, and why is it so important? How to implement a real-time analytics use case using AWS and Snowflake. A demo of the implementation.

AWS

AWS Analytics Analytics Apache Kafka

Data Science Current

Apache Kafka use cases: Driving innovation across diverse industries

Streaming Machine Learning Without a Data Lake

Trending Sources

Top Big Data Tools Every Data Professional Should Know

What Are AI Credits and How Can Data Scientists Use Them?

Best Data Engineering Tools Every Engineer Should Know

11 Open-Source Data Engineering Tools Every Pro Should Use

Predicting the Future of Data Science

What is Data Ingestion? Understanding the Basics

Discover the Most Important Fundamentals of Data Engineering

A Comprehensive Guide to the main components of Big Data

A Comprehensive Guide to the Main Components of Big Data

Training Models on Streaming Data [Practical Guide]

A Simple Guide to Real-Time Data Ingestion

How to Manage Unstructured Data in AI and Machine Learning Projects

The Evolution of Customer Data Modeling: From Static Profiles to Dynamic Customer 360

How to Build a Real-Time Data Analytics Platform with Snowflake and AWS

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