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By SQream,

2024 State of Big Data Analytics

Survey Report, June 2024: Constant Compromising Is Leading to Suboptimal Results

Introduction & Methodology

The rapid growth in generative AI over the past couple of years has resulted in the need to analyze massive (and growing) volumes of data. As a company that provides enterprises with critical business intelligence from massive data stores, we were keen to explore how this rapid growth in GenAI has impacted big data analytics in 2024.

The aim of this survey was therefore to better understand the connection between the cost of analytics and the results of analytics (cost-performance), to identify the primary pain points and
challenges currently facing those who work in the analytics space, and to discover the methods organizations are using to address these challenges.

The report is aimed at team leaders, CIOs, heads of data and other data-oriented professionals in large to very large organizations (500+ employees).

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Ohad Shalev

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The rapid growth in generative AI over the past couple of years has resulted in the need to analyze massive (and growing) volumes of data. As a company that provides enterprises with critical business intelligence from massive data stores, we were keen to explore how this rapid growth in GenAI has impacted big data analytics in 2024.

The aim of this survey was therefore to better understand the connection between the cost of analytics and the results of analytics (cost-performance), to identify the primary pain points and challenges currently facing those who work in the analytics space, and to discover the methods organizations are using to address these challenges. The report is aimed at team leaders, CIOs, heads of data and other data-oriented professionals in large to very large organizations (500+ employees). Subscribe to read the full report

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