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8 data strategy mistakes to avoid

CIO Business Intelligence

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

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Your Effective Roadmap To Implement A Successful Business Intelligence Strategy

datapine

1) What Is A Business Intelligence Strategy? 2) BI Strategy Benefits. 4) How To Create A Business Intelligence Strategy. Over the past 5 years, big data and BI became more than just data science buzzwords. Your Chance: Want to build a successful BI strategy today? What Is A Business Intelligence Strategy?

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Innovative data integration in 2024: Pioneering the future of data integration

CIO Business Intelligence

In the age of big data, where information is generated at an unprecedented rate, the ability to integrate and manage diverse data sources has become a critical business imperative. Traditional data integration methods are often cumbersome, time-consuming, and unable to keep up with the rapidly evolving data landscape.

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The success of GenAI models lies in your data management strategy

CIO Business Intelligence

How will organizations wield AI to seize greater opportunities, engage employees, and drive secure access without compromising data integrity and compliance? While it may sound simplistic, the first step towards managing high-quality data and right-sizing AI is defining the GenAI use cases for your business.

Strategy 143
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How AI orchestration has become more important than the models themselves

CIO Business Intelligence

Applying customization techniques like prompt engineering, retrieval augmented generation (RAG), and fine-tuning to LLMs involves massive data processing and engineering costs that can quickly spiral out of control depending on the level of specialization needed for a specific task. To learn more, visit us here.

Modeling 116
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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO Business Intelligence

Managing the lifecycle of AI data, from ingestion to processing to storage, requires sophisticated data management solutions that can manage the complexity and volume of unstructured data. As the leader in unstructured data storage, customers trust NetApp with their most valuable data assets.

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Data’s dark secret: Why poor quality cripples AI and growth

CIO Business Intelligence

I aim to outline pragmatic strategies to elevate data quality into an enterprise-wide capability. However, even the most sophisticated models and platforms can be undone by a single point of failure: poor data quality. This challenge remains deceptively overlooked despite its profound impact on strategy and execution.