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Innovative data integration in 2024: Pioneering the future of data integration

CIO

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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How Industry 4.0 Changes Predictive Maintenance From Mobile Apps And What It Means For The Future ?

OTS Solutions

has been transforming the manufacturing sector through the integration of advanced technologies such as artificial intelligence, the Internet of Things, and big data analytics. and Big Data Analytics in Predictive Maintenance Industry 4.0 is also enabling the use of big data in predictive maintenance.

Mobile 130
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The 10 most in-demand tech jobs for 2023 — and how to hire for them

CIO

But 86% of technology managers also said that it’s challenging to find skilled professionals in software and applications development, technology process automation, and cloud architecture and operations. Companies will have to be more competitive than ever to land the right talent in these high-demand areas.

LAN 358
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4 Megatrends in Big Data in 2019 and Beyond

Agile Engine

2018 was the second consecutive year when Gartner published an obituary of Big Data. No one, including Gartner, thinks Big Data is dead. Au contraire, Big Data has grown so ubiquitous it became “just data”, argue the authors of the obituaries. Trend 1: From Big Data to “Just Data”.

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Why You Want To Use Looker Studio For Data Visualization on BigQuery

Perficient

If you have built or are building a Data Lake on the Google Cloud Platform (GCP) and BigQuery you already know that BigQuery is a fully managed enterprise data warehouse that helps you manage and analyze your data with built-in features like machine learning, geospatial analysis, and business intelligence.

Data 111
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Kubernetes for Big Data Workloads

Abhishek Tiwari

In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. In fact, if we go by current trends containerised microservices running on Kubernetes are the future. Key challenges.

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Why Java is Still Relevant 30 Years Later

Mentormate

In the fast-paced world of technology, trends shift quickly. Additionally, Java’s modular architecture and well-defined APIs help facilitate easy extension and alteration of the codebase, making it adaptable to evolving requirements. But what makes it so enduring?