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10 Examples of How Big Data in Logistics Can Transform The Supply Chain

datapine

The big data market is expected to exceed $68 billion in value by 2025 , a testament to its growing value and necessity across industries. According to studies, 92% of data leaders say their businesses saw measurable value from their data and analytics investments.

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The Impact of Healthcare BI Tools on Decision-Making and Patient Care

FineReport

The implementation of robust healthcare data management strategies is imperative to mitigate the risks associated with data breaches and non-compliance. Furthermore, maintaining data security and compliance requires continuous vigilance and proactive measures to safeguard against potential vulnerabilities.

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Quantitative and Qualitative Data: A Vital Combination

Sisense

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

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Smart manufacturing technology is transforming mass production

IBM Big Data Hub

In smart factories, IIoT devices are used to enhance machine vision, track inventory levels and analyze data to optimize the mass production process. Artificial intelligence (AI) One of the most significant benefits of AI technology in smart manufacturing is its ability to conduct real-time data analysis efficiently.

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Buy Your Embedded Analytics and Empower Your End-Users With the Right Data

Jet Global

Market Drivers and Current Trends Organizations are increasing focus on the potential value within big data, seeking to better understand their customers and improve their products. The challenge is collecting all that data into one place and making it understandable. Need their analytics to scale reliably with their app or software.

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How to choose the best AI platform

IBM Big Data Hub

Enhanced security Open source packages are frequently used by data scientists, application developers and data engineers, but they can pose a security risk to companies. The best AI platforms typically have various measures in place to ensure that your data, application endpoints and identity are protected.

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The Gartner 2021 Leadership Vision for Data & Analytics Leaders Webinar Q&A

Andrew White

But we also know not all data is equal, and not all data is equally valuable. Some data is more a risk than valuable. Additionally, the value of data may change, and our own personal judgement of the the same data and its value may differ. Risk Management (most likely within context of governance).