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Digital Transformation: is your company data organised and ready for AI?

we specialise in helping organisations get their data organised

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Building a Strategic Data Organisation for AI Success

Setting up a Strategic Data Organisation to fuel your AI Strategy. It may seem obvious, but
setting up a Strategic Data Organisation is the necessary solid foundation needed for
running AI successfully in your organisation. Enabling staff members to access relevant
quality data in a timely manner is the key to unlocking the many benefits of AI.

The aim is to be the internal data provider of choice within the firm by:

  • employing governance best practices
  • providing high-quality products and services
  • being technically proficient

Addressing the data needs within the organisation in a holistic way helps reduce costs and
improve customer satisfaction

We look at three key dimensions in developing a Strategic Data Organisation for a client.

  1. Data Governance and Management
  2. Data Quality
  3. Technical SLAs

To read more and download the whitepaper on how we can build a strategic data organisation
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    Overview

    Key Dimensions for your Data organisation

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    Strategy

    • We have a strategy framework that sets up your programme for success.
    • The strategy encompasses the business objective, defining a framework before looking at communications and other key considerations.
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    Change Structure

    • Setting up and managing the formal part of the AI project to ensure the strategy is realized.
    • Suitable for Agile implementation.
    • Ensuring appropriate checkpoints and revisions are in place to regularly keep up to date as this rapidly changing part of the tech world keeps evolving.
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    People

    • Skills – Do you have or how do you get the right people with the right skills for your program to kickstart and ongoing?
    • Culture – Is your organization set up with a culture suitable for AI adoption, or is it resistant? Culture change needs to be included.
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    Data

    • The critical dimension for any AI model: sourcing the data, cleaning it, and managing it is essential to get a good outcome from AI.
    • Legal and ethical considerations around data are a huge topic, and one that will regularly play out (e.g., using copyrighted data to train models).
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    Technology

    • Foundation Model – Which model for what outcome? (OpenAI, Anthropic, Llama, etc.)
    • AI Platform – To train models, integrate with LLMs, and manage output.
    • Cloud infrastructure – Azure, AWS, Google Cloud, Oracle Cloud for storage and networking.
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    Governance

    • Managing both the use and updating of AI models.
    • Ensuring legal and cybersecurity are well managed.
    • Any AI system needs to be accountable, fair, deal with privacy and security issues, and comply with any regulatory framework.
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