IBM Journey to AI blog

NOVEMBER 3, 2023

It allows your business to ingest continuous data streams as they happen and bring them to the forefront for analysis, enabling you to keep up with constant changes. Apache Kafka boasts many strong capabilities, such as delivering a high throughput and maintaining a high fault tolerance in the case of application failure.

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Apache Kafka Data Warehouse Data Pipeline Big Data 79

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. He addressed challenges in data replication and offered solutions to optimize these processes.

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Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

Data Pipeline 52

Data Pipeline Data Quality Database Apache Kafka 52

Women in Big Data

OCTOBER 9, 2024

The success of any data initiative hinges on the robustness and flexibility of its big data pipeline. What is a Data Pipeline? A traditional data pipeline is a structured process that begins with gathering data from various sources and loading it into a data warehouse or data lake.

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Big Data Big Data Apache Kafka Data Pipeline 59

ODSC - Open Data Science

FEBRUARY 6, 2024

Spark offers a versatile range of functionalities, from batch processing to stream processing, making it a comprehensive solution for complex data challenges. Apache Kafka For data engineers dealing with real-time data, Apache Kafka is a game-changer.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

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. ETL is vital for ensuring data quality and integrity. from 2025 to 2030.

Data Engineer 52

Data Engineer Data Engineering Data Engineering Data Engineering 52

The MLOps Blog

MARCH 15, 2023

In this post, you will learn about the 10 best data pipeline tools, their pros, cons, and pricing. A typical data pipeline involves the following steps or processes through which the data passes before being consumed by a downstream process, such as an ML model training process.

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Data Pipeline ETL SQL Data Quality 59