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Real-time artificial intelligence and event processing  

IBM Big Data Hub

Non-symbolic AI can be useful for transforming unstructured data into organized, meaningful information. This helps to simplify data analysis and enable informed decision-making. Events as fuel for AI Models: Artificial intelligence models rely on big data to refine the effectiveness of their capabilities.

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Data governance use cases – 3 ways to implement

Collibra

However, once you have a system of record in place for your data, your organization can implement many valuable data governance use cases more easily. . In this post, we’ll highlight the top three most valuable data governance use cases. The data structure and requirements are not defined until the data is needed.

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The CFO’s role in the age of generative AI

IBM Big Data Hub

A generative AI agent or assistant can ingest and summarize structured and unstructured data from internal and external sources, parse through it and generate insights and patterns for financial information that can drive business value and potentially identify untapped revenue streams.

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Key steps on the road to LGPD compliance

Thales Cloud Protection & Licensing

Additionally, organizations are obligated to report any data security incidents or breaches to Brazilian national authorities. It is advantageous to automate the process… considering all the data stores in scope (including local, network, database, big data and cloud) and to cover both structured and unstructured data types.

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Will generative AI make the digital twin promise real in the energy and utilities industry?

IBM Big Data Hub

Digital twins and integrated data For the presentation layer, you can leverage various capabilities, such as 3D modeling, augmented reality and various predictive model-based health scores and criticality indices.

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Data architecture strategy for data quality

IBM Big Data Hub

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

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5 fundamental questions for your data journey

IBM Big Data Hub

To accelerate its journey to AI, a data-driven organization needs a trusted data foundation that empowers information stakeholders. Stakeholders need the ability to discover, understand, integrate, analyze, govern and self-serve structured and unstructured data — on premises, on cloud, and hybrid — at any scale.