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Digital KPIs: The secret to measuring transformational success

CIO Business Intelligence

Regardless of where organizations are in their digital transformation, CIOs must provide their board of directors, executive committees, and employees definitions of successful outcomes and measurable key performance indicators (KPIs). He suggests, “Choose what you measure carefully to achieve the desired results.

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Data Maturity Models | Measure The Health Of Your Data

Anmut

Data maturity models are a crucial step for any organisation looking to improve their data, informing if your current data practices are helping, or holding back, your business. ? Click the links below to navigate to different sections What are data maturity models? Why do we need data maturity models? It’s like driving a car.

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How to get your CFO to buy into a better model for IT funding

CIO Business Intelligence

Modern digital organisations tend to use an agile approach to delivery, with cross-functional teams, product-based operating models , and persistent funding. But to deliver transformative initiatives, CIOs need to embrace the agile, product-based approach, and that means convincing the CFO to switch to a persistent funding model.

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Getting specific with GenAI: How to fine-tune large language models for highly specialized functions

CIO Business Intelligence

Large language models (LLMs) are hard to beat when it comes to instantly parsing reams of publicly available data to generate responses to general knowledge queries. Moreover, challenges around data privacy and recognition of intellectual property often require a level of transparency that simply does not exist in many off-the-shelf models.

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Achieving cloud excellence and efficiency with cloud maturity models

IBM Big Data Hub

Cloud maturity models are a useful tool for addressing these concerns, grounding organizational cloud strategy and proceeding confidently in cloud adoption with a plan. Cloud maturity models (or CMMs) are frameworks for evaluating an organization’s cloud adoption readiness on both a macro and individual service level.

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Top 8 failings in delivering value with generative AI and how to overcome them

CIO Business Intelligence

Generative AI (GenAI) is rapidly emerging as a game changer for enterprises, but turning its potential into measurable value remains a significant challenge. Data privacy and compliance issues Failing: Mismanagement of internal data with external models can lead to privacy breaches and non-compliance with regulations.

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Develop a business chargeback model within your organization using Amazon Redshift multi-warehouse writes

AWS Big Data

Other benefits include the ability to monitor and control costs for each data warehouse, and enabling data collaboration across different teams because you can write to each other’s databases. As organizations continue to migrate workloads to AWS, they are also looking for mechanisms to manage costs efficiently.