Remove Cybersecurity Remove Data Management Remove Supply Chain
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How to Make Sure Your IoT Systems Stay Compliant

Smart Data Collective

Sometimes, developers could make mistakes when creating IoT hardware and software, which could put the organization at risk of cybersecurity threats. Another common cybersecurity threat is using inappropriate technology. Adding security features, such as functionality to encrypt stored data is another way to improve cybersecurity.

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AI and GenAI for Manufacturing and Supply Chains

GAVS Technology

While technology innovations like AI evolve and become compelling across industries, effective data governance remains foundational for the successful deployment and integration into operational frameworks. These steps help mitigate risks associated with data security while leveraging AI technologies.

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150+ Top Global Cloud Thought Leaders and Next Generation Leaders of 2021

Whizlabs

Mark Lynd – Cloud Thought Leader and Keynote Speaker for Cybersecurity, AI & IoT, Head of Digital Business CISSP, ISSAP & ISSMP. Helen’s expertise ranges from digital transformation, AI, cloud computing, Cybersecurity, IoT and Marketing and she has been recognized as a global thought leader in all these areas.

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Exploring Data Provenance: Ensuring Data Integrity and Authenticity

Astera

Data Provenance is vital in establishing data lineage, which is essential for validating, debugging, auditing, and evaluating data quality and determining data reliability. Data Lineage vs. Data Provenance Data provenance and data lineage are the distinct and complementary perspectives of data management.

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BFSI: Banking, Financial Services and Insurance

The BAWorld

The BFSI market is expected to employ over 55 million people globally by 2025 ( Source: Deloitte ) Data Management and Security: BFSI institutions engage and keep the different kinds of personal and financial data where the IT industry implements cybersecurity measures, secure data storage, and faster data processing systems to ease performance.

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Generative AI in 2024: A Strategic Guide for Global Enterprises

Cprime

How does generative AI influence data management in enterprises? – Generative AI enables enterprises to process unstructured data, unlocking new business value and sparking advances across organizational functions. This should involve not just IT teams, but also cybersecurity, legal, risk management, and HR specialists.

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Top 5 Trends Impacting Finance Teams in 2024

Insight Software

Migration to Cloud: Consolidating Different Data Sets Download Now 4. Cybersecurity and Data Privacy This year, we predict a heightened focus on maintaining data privacy and security in finance. Securities and Exchange Commission’s new rules for cybersecurity incident disclosure. Why is this?

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