Welcome to ClaroMente: The Clarofy Information Hub!

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    Knowledge Base

     
    In this section we will take you through a typical data science workflow. We will dive a bit deeper into each step and will provide you with hints about what to look for. 

    Clarofy Features

     
    Here we will dive into Clarofy features, explain how they work, what to use them for, and how each one of them can help you bring value to your operation.

    Knowledge base

    In this section we will take you through a typical data science workflow. We will dive a bit deeper into each step and will provide you with hints about what to look for. 

    The workflow will follow the steps below.

    Workflow

    The above stages are at the center of the Clarofy app - a typical analytics project makes most sense when done within a structured process like the above.

    KNOWLEDGE BASE

    Business Understanding: Verify a hypothesis

    Having a hypothesis before starting an analytics project is critical.

    Before we plunge into an analytics project, it's important to ask questions and discuss the 'business understanding' with all the major stakeholders. This is essentially an exercise to define the question: What is the problem we are trying to solve, or what is the opportunity we are trying to uncover? Hearing the answer to that from the Product owner or other stakeholder clarifies the goal of the projects and is an anchor for any work.

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    KNOWLEDGE BASE

    Connect your data: Upload a dataset

    How do we get data into our analysis tool?

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    KNOWLEDGE BASE

    Select your data: How many tags/variables are too many?

    Stay away from the dreaded 'scope-creep'

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    KNOWLEDGE BASE

    Prepare your data

    What needs to be done before data is ready for analysis?

     

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    KNOWLEDGE BASE

    Explore your data

    Visualise your data so you can see overarching trends.

     

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    KNOWLEDGE BASE

    Exploration graphs

    So many graph types - which is the most useful?

     

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    KNOWLEDGE BASE

    Analyse your data

    Let's test relationships and measure their significance.

     

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    KNOWLEDGE BASE

    Evaluate your data

    Value a potential change and make data-driven decisions.

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    KNOWLEDGE BASE

    Deploy your data

    Take action and solve the problem.

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    KNOWLEDGE BASE

    Linear Regression

    What is it and why is it important?

    Coming Soon
    KNOWLEDGE BASE

    Time Series

    How to analyse continuous data

    Coming Soon

    Clarofy features

    Here we will dive into Clarofy features, explain how they work, what to use them for, and how each one of them can help you bring value to your operation.

    CLAROFY FEATURES

    How to use the Exploration features to pick up relationships and trends in your data

    The Exploration Plots page allows you to investigate and discover trends, relationships, inflection points and other intricacies in your data.

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    Integ2
    CLAROFY FEATURES

    Heatmaps

    What are they and how can they help you

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    CLAROFY FEATURES

    Correlation

    Find out which variables are affecting others

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    CLAROFY FEATURES

    Validation

    Upload and validate your dataset

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    CLAROFY FEATURES

    CUSUM

    Monitor shifts in your variable mean.

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    CLAROFY FEATURES

    Create a Model

    How can I simulate behaviour with a mathematical model?

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    CLAROFY FEATURES

    Evaluate your data

    Make decisions about the 'population'.

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    CLAROFY FEATURES

    Activity Log

    Keep track of your workflow

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    CLAROFY FEATURES

    Pi Integration

    Connect to your onsite historian

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    CLAROFY FEATURES

    Regression

    Create a model in Clarofy

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    CLAROFY FEATURES

    Filtering

    Easy filtering for quick analysis in Clarofy

    Coming Soon