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Online Orientation Session on

How to Use Analytics to Succeed as an Organisation?

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  • About the Webinar


    60 mins


    July 6, 2019


    11:00 am

    Who is the Speaker?

    Praveen is results-driven digital analytics professional with rich experience in managing and delivering to large Retail, Insurance, Telco, and software houses in digital space.

    He has over 12+ years of eclectic experience in Global account management (client engagement), Operations management (global delivery teams), Transition management Team building and people management. He is passionate about simplifying complex digital marketing and analytics execution through efficiency accelerators.

    He has successfully deployed multiple global operations for top Fortune 100 clients across industries & had built models and data architectures covering wide range complex data set.

    Praveen Sathyadev

    Key Takeaways
    • Analytics is a journey and not a destination – patience is a virtue.
    • Money can possibly buy happiness but not analytics
    • How to get started if you are a novice or how to course-correct if you have taken a path that is never-ending.
    • Checklist for ‘Are you ready for advanced analytics?’
    • How to staff for your analytics organization?
    • How to evangelize analytics?

    Session Agenda

    Data, analytics and AI are amongst the most misunderstood terms in the industry. Per my experience, over 60% to 75% analytics investments have never seen fruition due to various factors including corporate ignorance and arrogance.

    While it is cool to have an analytics function within the organisation, it is even more imperative to analyse your investments before plunging. The industry is overwhelmed with too many players and influencers. This has led to a mad rush towards analytics with little or no understanding of the building blocks of this ‘Must Have’ domain.

    Who Should Attend?


    Computer Science Graduates

    Aspiring Machine Learning Engineers


    Aspiring Data Analysts

    Aspiring Data Scientists

    Software Engineers