Business of Insights Topic What and Why Balaji
Business of Insights ! Topic : What and Why? Balaji S. Thiruvenkatachari June 2020
Course : Data Science & Analytics Mastery Module M 1 - Data Science and Analytics : Opportunity and Landscape Lesson L 4 - Capabilities Needed Learning Outcome A Data Scientist has been portrayed as an ‘Unicorn’ role. There is some truth to this but for vast majority of business need, core data science capability can be very well mastered. In this course we distill the key capabilities need and details so that you can leverage your strengths coupled with Data Scientist role needs to fast track you career.
Confluence of four Business-Technology capabilities According to IDC: “[I]f our digital universe or total data content were represented by tablets, then by 2020 they would stretch all the way to the moon over six times. That’s equal to 44 zettabytes of data, or 44 trillion gigabytes. ” …. . is powering this disruption creating a flywheel effect!
World around us is changing rapidly, impacting all ! “Data” : On back of ever increasing quantity of powerful data Algorithms and Platforms are shaping our lives Accelerated by wider access to cheaper computing Power AInsights at the Core • • “Learning” based shift – Patterns, experiments “What data tells me” vs. “Rules” based BInnovation & New Models • • New Economy Models (FAANG) Multiple examples (including sharing economy etc. )
Insights Powered Business Transformation is a Team effort : PODs e. g. “Build with Business” Business Insights (Interfacing) Solution(s) § Value (Strategic) : Direction, business case, Applied and acceptance focus § Governance(Priorities): What to solve, Ethics etc. . § Organization (Adoption) : People, process etc. . § Example Roles: § Stakeholders, Domain SMEs, BAs, Product Owners (Agile) Engineering (Engine) “Science and Art : Insights” § Systematic : Problem, Use case, design think. . § Core Expertise: Using Techniques, assets (data, digital etc. ), experience to derive solutions (Models, Apps etc. ) § Outcome & Ongoing : Learn, interpret, apply, Experiment. . § Example Roles: § Data Scientists, AI / ML SMEs etc. . “Engineering” : Foundation for Speed & Scale § Engine : Foundational Capability for running a predictable engine § Architecture: Technology + Tools + Process, Platform etc…enabled § Services & Mindset: Run, measure, course correct, keep it alive etc…Predictability to scaling § Example Roles: Data Engineers, Bigdata SME, Automation, Data Management, Cloud SME Insights at scale needs a different mindset : Business Applied focus powered by well-oiled engine !
Skills Needed for a well-rounded Insights professional ! Communication (e. g. Storytelling) Business Skills Mindset: Applied & Scale IT / Engineering Skills Analytics Skills “Data” / Data management Skills “Problem Solving” aptitude and ability is key !
Thank you ! www. Business. Of. Insights. com Insights Community Sharing Blogs Perspectives Formal Learning (Courses) Latest Happenings Balaji S. Thiruvenkatachari stbalaji@business. Of. Insights. com 9840768200 AI for Good Giving back
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