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Data Strategy

Data Strategy and Governance

Discover essential resources for building and implementing effective data strategies in your organisation. From data governance frameworks to fostering data literacy, we provide comprehensive guidance on creating a data-driven culture.

Our data strategy content covers critical topics including data governance, data security and privacy, DataOps practices, data platform architecture, and building robust data warehouses. Learn how to establish proper data collection and storage practices, ensure data quality, and implement security measures that protect sensitive information.

Whether you’re developing your first data strategy or maturing existing data capabilities, our resources help you navigate challenges around data culture, literacy, and science. We focus on practical approaches that balance innovation with responsible data management, helping organisations unlock the full value of their data assets through business intelligence, analytics, and effective visualisation.

Europe’s Digital Strategy and Manufacturing

Europe’s Digital Strategy and Manufacturing

Data in manufacturing could have a net benefit of €1.5 trillion by 2027 so the European Digital Strategy needs to help realise that benefit. The strategy will help make common data spaces available and support cloud infrastructures to assist manufacturers.

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Investing in tools scales staff productivity

Investing in tools scales staff productivity

Businesses with the highest productivity experience more stable and consistent revenue growth, as well as being able to adapt more quickly. With less waste and more staff power focussed on growth, manufacturers with an investment in tooling are more operationally resilient.

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Chatbots explained

Chatbots explained

Chatbots are computer programmes that provide a (primarily) text-based interface to help people access information or perform tasks. Chatbot conversations can help you improve customer service whilst reducing demand on staff. They can process text using natural language processing and build a conversational workflow to support a intuitive interaction with people.

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How to move your operations to the cloud - what you need to know

How to move your operations to the cloud - what you need to know

You’ve probably heard of the cloud but what is it and how can it help your business? Learn how moving to the cloud can help you innovate and stay ahead of the curve when it comes to tech.

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Tools matter for Developer Velocity

Tools matter for Developer Velocity

Businesses with the highest developer velocity experience the highest revenue growth, according to new research by Microsoft and McKinsey. Read on to understand how tools impact developer velocity and what the business case is for investing in them.

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Developer Velocity

Businesses with the highest developer velocity experience the highest revenue growth, according to new research by Microsoft and McKinsey. Read on to understand the factors impacting developer velocity and how you can start building a strategy to improve this vital area of technology in your business.

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Selected for Procter & Gamble Supplier Academy 2021

Selected for Procter & Gamble Supplier Academy 2021

The Procter & Gamble Supplier Academy is a partnership between P&G and WEConnect International, providing training for majority women-owned businesses.

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Funding for AI use cases and much more - AIPlan4EU

Funding for AI use cases and much more - AIPlan4EU

At Nightingale HQ we recently submitted our AI use-cases to the AIPlan4EU to potentially develop them further. Find out how you can get yours funded and all about the new European AI on Demand Platform.

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Manufacturers: Are you digitising or digitalising?

To digitise your business means to perform traditionally analogue processes or actions digitally. Rather than a few changes here and there, digitalisation involves a change in how to the process is performed to better leverage technology.

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MLOps is like process engineering for Data Science

MLOps is like process engineering for Data Science

The goal of MLOps is to streamline the development, deployment, and operation of machine learning models, by supporting their building, testing, releasing, monitoring, performance tracking, reusing, maintenance and governance, joining the efforts of Data Science and IT teams under a shared focus.

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