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    BARRI.CC

    Exxelia Part Number Data Science

    Data-Driven Part Number Generation for Exxelia's Strategic Marketplace Expansion

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    Engineered a data science solution using Python and Deepnote to systematically generate millions of structured Part Numbers (PNs), enabling Exxelia to list its catalogue products on major marketplaces like Digikey and Arrow, thereby significantly enhancing brand visibility and market reach.

    Python | Deepnote | Data manipulation libraries (e.g., Pandas, NumPy) | ERP System Data

    Transitioned Exxelia from a reactive, order-based Part Number (PN) creation system to a proactive strategy essential for marketplace integration. Addressed the complex data science challenge of identifying suitable catalogue products and then generating millions of accurately structured PNs, particularly for extensive product lines like ceramic capacitors. This overcame a critical barrier to entry for key digital sales channels, paving the way for increased brand awareness and product discoverability.

    #AI & DATA FOR GROWTH MARKETING

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    #AI & DATA FOR GROWTH MARKETING

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    #AI & DATA FOR GROWTH MARKETING

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    #AI & DATA FOR GROWTH MARKETING

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    #AI & DATA FOR GROWTH MARKETING

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    #AI & DATA FOR GROWTH MARKETING

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    ✦ My Process

    In-depth Audit

    I begin with a data-driven audit to understand your business, systems, and goals.

    Strategy and Planning

    I craft a tailored plan focused on impactful, goal-aligned solutions.

    Integration

    I implement and integrate the solution seamlessly into your workflows.

    Key Features

    Developed a data science methodology to analyze existing product data and determine optimal catalogue selections for marketplace listing.

    Utilized Python and Deepnote to build a scalable and efficient process for generating millions of unique and structured Part Numbers.

    Ensured the generated PN data structures were compliant with the specific requirements of major electronic component marketplaces (e.g., Digikey, Arrow).

    Leveraged ERP data as a foundational source for understanding existing product parameters and informing the generation logic.

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