Remove Data Lake Remove Data Strategy Remove Internet of Things
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Optimizing a Centralized Approach for the Modern Distributed Data Estate

CIO Business Intelligence

With the focus shifting to distributed data strategies, the traditional centralized approach can and should be reimagined and transformed to become a central pillar of the modern IT data estate. billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge.

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Achieving Trusted AI in Manufacturing

Cloudera

According to Gartner , 80 percent of manufacturing CEOs are increasing investments in digital technologies—led by artificial intelligence (AI), Internet of Things (IoT), data, and analytics. Trusted AI begins with trusted data What resolves the data challenge and fuels data-driven AI in manufacturing?

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Creating Data Value With a Decentralized Data Strategy

CIO Business Intelligence

For decades organizations chased the Holy Grail of a centralized data warehouse/lake strategy to support business intelligence and advanced analytics. billion connected Internet of Things (IoT) devices by 2025, generating almost 80 billion zettabytes of data at the edge. You have to automate it.

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It’s not your data. It’s how you use it. Unlock the power of data & build foundations of a data driven organisation

CIO Business Intelligence

To meet these demands many IT teams find themselves being systems integrators, having to find ways to access and manipulate large volumes of data for multiple business functions and use cases. Without a clear data strategy that’s aligned to their business requirements, being truly data-driven will be a challenge.

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Amazon Kinesis Data Streams: celebrating a decade of real-time data innovation

AWS Big Data

With data streaming, you can power data lakes running on Amazon Simple Storage Service (Amazon S3), enrich customer experiences via personalization, improve operational efficiency with predictive maintenance of machinery in your factories, and achieve better insights with more accurate machine learning (ML) models.

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Unlock scalability, cost-efficiency, and faster insights with large-scale data migration to Amazon Redshift

AWS Big Data

We can determine the following are needed: An open data format ingestion architecture processing the source dataset and refining the data in the S3 data lake. This requires a dedicated team of 3–7 members building a serverless data lake for all data sources. Vijay Bagur is a Sr.

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Building Better Data Models to Unlock Next-Level Intelligence

Sisense

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021! Discover why.