Dataconomy

MAY 26, 2017

Amazon Kinesis is a platform to build pipelines for streaming data at the scale of terabytes per hour. The post Amazon Kinesis vs. Apache Kafka For Big Data Analysis appeared first on Dataconomy. Parts of the Kinesis platform are.

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Apache Kafka Data Analysis Data Analysis Big Data 155

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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Apache Kafka Internet of Things Data Pipeline Clustering 58

Women in Big Data

OCTOBER 9, 2024

These procedures are central to effective data management and crucial for deploying machine learning models and making data-driven decisions. The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline?

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Big Data Big Data Apache Kafka Data Pipeline 59

Pickl AI

NOVEMBER 4, 2024

Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering? Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. Data pipelines are significant because they can streamline data processing.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

Pickl AI

DECEMBER 9, 2024

Batch processing handles large datasets collected over time, while real-time processing analyses data as it is generated. What are the Key Features of Apache Hive? Hive provides SQL-like querying, schema-on-read functionality, and compatibility with Hadoop for large-scale Data Analysis. Explain the Role of Apache HBase.

Big Data 52

Big Data Big Data Hadoop Apache Kafka 52

Dataconomy

FEBRUARY 23, 2023

Data engineers play a crucial role in managing and processing big data Ensuring data quality and integrity Data quality and integrity are essential for accurate data analysis. Data engineers are responsible for ensuring that the data collected is accurate, consistent, and reliable.

Data Engineer 91

Data Engineer Data Engineering Data Engineering Data Engineering 91

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? Happy Learning!

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Machine Learning Machine Learning Data Pipeline Apache Kafka 72