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    Objectives


    • Key data analysis and analytical strategies
    • Link data and analytics to business goals and objectives.
    • Increasing reliance on data and analytics
    • Ask good questions of the data to obtain information from the data.
    • Initiate the process of constructing and using the data narrative
    • Creating a culture of data literacy

    Agenda



    • Part 1 -Overview of data literacy
    • Current state of data in the world
    • Data structure and trust in organizations
    • Democratization of data
    • The four levels of analysis and analytical strategy
    • Defining and learning about data literacy and its features
    • Part 2 - Data Literacy Culture
    • Value of data literacy for organizations
    • The role of leadership in data and analytics.
    • Key characteristics of a data literacy culture
    • The role of the ChiefData Officer
    • Part 3 - Data-driven decision making
    • Framework for data-driven decision making
    • Six-phase approach to data-driven decision making
    • Learning to ask good questions with data
    • Apply mental models to decision-making.

    Addressed to


    • People who use data to help make decisions in an organization.

    Requirements



    • Basic knowledge of business intelligence.
    • It is recommended that students are familiar with and understand the key features of their data.
    Qlik Cloud Assistant