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

CIO Business Intelligence

These strategies, such as investing in AI-powered cleansing tools and adopting federated governance models, not only address the current data quality challenges but also pave the way for improved decision-making, operational efficiency and customer satisfaction. When customer records are duplicated or incomplete, personalization fails.

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Have we reached the end of ‘too expensive’ for enterprise software?

CIO Business Intelligence

Generative artificial intelligence ( genAI ) and in particular large language models ( LLMs ) are changing the way companies develop and deliver software. The commodity effect of LLMs over specialized ML models One of the most notable transformations generative AI has brought to IT is the democratization of AI capabilities.

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CIO metrics are failing digital transformation; it’s time to radically rethink success

CIO Business Intelligence

The status of digital transformation Digital transformation is a complex, multiyear journey that involves not only adopting innovative technologies but also rethinking business processes, customer interactions, and revenue models.

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Writing Business Cases: 6 Things You Should Know About Identifying Project Benefits

BA Learnings

Understand the current state and document current key performance indicators to ensure benefits can be measured after the project is implemented. They require a supporting benefits realization model or framework to ensure benefits identified in the business case can be reaped and measured further down the track.

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Managing machine learning in the enterprise: Lessons from banking and health care

O'Reilly on Data

In recent posts, we described requisite foundational technologies needed to sustain machine learning practices within organizations, and specialized tools for model development, model governance, and model operations/testing/monitoring. Sources of model risk. Model risk management. Image by Ben Lorica.

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Using Analytics to Maximize Revenue with a SaaS Business Model

Smart Data Collective

Data analytics technology is becoming a more important aspect of business models in all industries. The importance of customer loyalty and customer service has become increasingly well-known and companies have needed to adapt their business models accordingly to gain a competitive edge. This is a key stage for customer retention.

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AI Product Management After Deployment

O'Reilly on Data

Similarly, in “ Building Machine Learning Powered Applications: Going from Idea to Product ,” Emmanuel Ameisen states: “Indeed, exposing a model to users in production comes with a set of challenges that mirrors the ones that come with debugging a model.”.