Open Analytics - 7. Ethereum

    Submit a deep dive dashboard that explores a specific topic in detail using Ethereum data.

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    Open Analytics (OA) bounties are bounties without specific prompts, just a direction and a reward. It’s your chance to have your brain follow your heart — got a spark of interest, or a loose thread, or a weirdly-specific question gnawing at the back of your mind? Follow it as far as you can!

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    How do you raise your dashboard score?

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    The more accurate, detailed and the higher quality your dashboard (presentation, methodology, documentation, readability), the better your chances of scoring well. Here are a few rules of thumb for Open Analytics bounties:

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    DO:

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    • Give your dashboard a specific and relevant title
    • Go deep into a topic and find creative/unusual data or paradigms
    • Find macro and/or micro trends within a particular group or platform
    • Ask weirdly-specific questions
    • Consider trends, news and hot topics of the past day(s), week(s), month(s)
    • Consider what info the platform’s core team and users would find valuable
    • Organize your dashboard so it’s easy to read through
    • Explain your methods clearly and check for mistakes (grammatical or statistical)
    • Consider what media (text/visual) and chart types best fit a certain metric/data point
    • Tweet your dashboard and/or make a thread about conclusions you may draw.

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    DON’T:

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    • Submit a dashboard with a generalized title like "Open Analytics Dashboard"
    • Make an overview/surface-level dashboard
    • Chart only basic data (# of transactions, users, validators, etc) Include inaccurate or false information
    • Copy other peoples’ work
    • Double-dip (submit a dashboard you’ve already submitted for any bounty program).
    • Re-submit prior work with only minimal updates.

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    Analysts in non-compliance with our policy on plagiarism may be exposed on Discord and see their xMetric slashed.

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    Introduction:

    🧠 Methodology:

    Overview

    This analysis includes the following categories:

    Section 1:

    📊Observations

    References:

    🔥Result and discussion🔥

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