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HEMA accelerates their data governance journey with Amazon DataZone

AWS Big Data

Initially, the data inventories of different services were siloed within isolated environments, making data discovery and sharing across services manual and time-consuming for all teams involved. Implementing robust data governance is challenging. Oghosa Omorisiagbon is a Senior Data Engineer at HEMA.

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Beyond the hype: Do you really need an LLM for your data?

CIO Business Intelligence

Even basic predictive modeling can be done with lightweight machine learning in Python or R. In life sciences, simple statistical software can analyze patient data. Its about investing in skilled analysts and robust data governance. We already have excellent tools for these tasks.

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Self-Serve Data Prep with Data Governance AND Agility!

Smarten

Self-Serve Data Prep: You Can Have Data Agility AND Data Governance! When you are considering an augmented analytics solution, you will want to look at the capabilities for self-serve data preparation (SSDP).

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CDOs: Your AI is smart, but your ESG is dumb. Here’s how to fix it

CIO Business Intelligence

Yet, while businesses increasingly rely on data-driven decision-making, the role of chief data officers (CDOs) in sustainability remains underdeveloped and underutilized. Investing in data science and AI for sustainability Advanced analytics and AI can unlock new opportunities for sustainability.

IT 59
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Cloudera AI Inference Service Enables Easy Integration and Deployment of GenAI Into Your Production Environments

Cloudera

It is a powerful deployment environment that enables you to integrate and deploy generative AI (GenAI) and predictive models into your production environments, incorporating Cloudera’s enterprise-grade security, privacy, and data governance. This is where the Cloudera AI Inference service comes in.

Metrics 73
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5 Data Governance Mistakes to Avoid

Alation

As firms mature their transformation efforts, applying Artificial Intelligence (AI), machine learning (ML) and Natural Language Processing (NLP) to the data is key to putting it into action quickly and effecitvely. Using bad data, or the incorrect data can generate devastating results. 5 common data governance mistakes 1.

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The role of IoT in shaping smart cities

CIO Business Intelligence

Raw data collected through IoT devices and networks serves as the foundation for urban intelligence. Advanced analytics platforms, leveraging machine learning (ML) algorithms and AI, extract meaningful insights from this data. These can even be visualized in 3D, providing a clear and intuitive understanding of the physical environment.

IoT 123