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Streaming Machine Learning Without a Data Lake

ODSC - Open Data Science

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.

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Data Version Control for Data Lakes: Handling the Changes in Large Scale

ODSC - Open Data Science

In the ever-evolving world of big data, managing vast amounts of information efficiently has become a critical challenge for businesses across the globe. As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident.

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Introducing The Streaming Datalake

insideBIGDATA

In this contributed article, Tom Scott, CEO of Streambased, outlines the path event streaming systems have taken to arrive at the point where they must adopt analytical use cases and looks at some possible futures in this area.

Analytics 363
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Interview – Business Intelligence und Process Mining ohne Vendor Lock-in!

Data Science Blog

Die Daten bereiten wir in sogenannte Event Logs, also Prozessprotokolle, auf und laden sie dann ein eines der vielen Process Mining Tools, egal in welches. Was gerade zum Trend wird, ist der Aufbau eines Data Lakehouses. Ein Lakehouse inkludiert auch clevere Art und Weise auch einen Data Lake.

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Sneak peek at Microsoft Fabric price and its promising features

Dataconomy

Unified data storage : Fabric’s centralized data lake, Microsoft OneLake, eliminates data silos and provides a unified storage system, simplifying data access and retrieval. OneLake is designed to store a single copy of data in a unified location, leveraging the open-source Apache Parquet format.

Power BI 194
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Drowning in Data? A Data Lake May Be Your Lifesaver

ODSC - Open Data Science

Data management problems can also lead to data silos; disparate collections of databases that don’t communicate with each other, leading to flawed analysis based on incomplete or incorrect datasets. One way to address this is to implement a data lake: a large and complex database of diverse datasets all stored in their original format.

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Driving Business Value and ROI from a Hybrid Cloud Data Lake

Alation

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. earthquake, flood, or fire), where the data collected does not need to be as tightly controlled.