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Webinar - Data Science Role in Industry 4.0

Webinar - Data Science Role in Industry 4.0

Fiqry Revadiansyah

May 05, 2021
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  1. Please call me Fiqry, no additional prefix/suffix on it. I

    currently working as a Data Science Analyst @Accenture Indonesia, previously worked as a RnD Data Science Mgr @Purwadhika, and a Data Scientist @Bukalapak Passionate on Data Analytics, Immersive Computing, Human-Centered Technologies, and e-Sport (of course!) GREETINGS! Fiqry Revadiansyah
  2. 04 01 02 03 Come join us, being an aspiring

    data scientist We breathe directly on Artificial Intelligence A brief summary of all talks! Here we lived, a place of nowhere to run TABLE OF CONTENTS THE OPPORTUNITY OUR CONTRIBUTION END STATEMENT AGE OF DISRUPTION
  3. DATA, UNEXPECTEDLY, FEED OUR LIFE: CLEAN EMAIL SIMILAR PRODUCT Gmail

    Automatic Spam Detector Amazon Similar Product Ads AUTO ROUTE Gojek Fastest Route Selection RECOMMENDATION Youtube Recommender System 03:00 12:00 18:00 07:00
  4. VISUAL DATA: HUMAN VISION Tesla provides autonomous driving system, help

    the people to drive and avoid the crash situation Technology: Computer Vision (CV) AUTONOMOUS DRIVING R-CNN ALGORITHM
  5. TEXT DATA: HUMAN LANGUAGE Gmail text recommendation, suggest mail words

    along with correct the spellings. Technology: Natural Language Processing (NLP) TEXT RECOMMENDATION BERT ALGORITHM
  6. AUDIO DATA: HUMAN SOUND Amazon alexa enables us to do

    something, such as playing music or turn on electronic devices based on our voice commands. Technology: Automated Speech Recognition (ASR) VOICE COMMAND ASR ALGORITHM
  7. DIGITAL ACCELERATION IN THE WORLD How money and human culture

    changed the world How world congress shaped the new world How academic contributed to the world movements How a war made world’s instability SOCIAL-ECONOMY WORLD WAR RESEARCH AND DEVELOPMENT POLITICAL WHEEL
  8. STEAM ENGINE 1780 - 1870 SOCIAL ECONOMY: INDUSTRIAL REVOLUTION ASSEMBLY

    LINE 1870 - 1950 AI & IOT 2010 - Now ROBOTICS & COMPUTER 1970 - Now 100 years on average Only 40 years VUCA firstly introduced in 1987 *Bennis, W. (1987)
  9. VUCA WORLD: STATEMENT OF SURVIVABILITY A condition to describe the

    current world situation after cold war, which is volatile, uncertain, too complex, and ambiguous (Bennis, W., 1987) VUCA WORLD (1987) OPEN INNOVATION FRUGAL INNOVATION COMMUNITY INNOVATION DISRUPTIVE INNOVATION
  10. DISRUPTIVE INNOVATION: AN ACCELERATION GEAR An innovation that creates a

    new market which eventually disrupts an existing market, displacing established market-leading firms, products, and alliances* DISRUPTIVE INNOVATION ENTRANTS INCUMBENTS
  11. QUALITY Compel high quality assurance and service to serve significant

    impact QUANTITY Supermassive service range, huge user distribution and affordable cost THE PRINCIPAL OF DISRUPTION INNOVATION TIME Relatively quick for adaptation and adoption
  12. RESEARCH AND DEVELOPMENT: EVOLUTION The Idea of Data-Driven decision is

    not exactly new, it is a human nature to make decision based on data. Our ancestors shown that they made a map of the world, using a clay tablet (700 - 500 BCE) Even in the early 18th centuries, people decided things using a back form of data, like paper to write and store information. CLAY TABLET
  13. EVOLVED TOOLS AND BIG DATA EMERGENCE Thanks to electricity invention,

    the first wave of technological advancement born in 1954 (First computer by IBM, IBM 650). Computer helps human to make a quicker decision making with abundant information. Right now, we have CPU, GPU, TPU, etc. As the computer wave arrived, the number of stored data also increased exponentially through time. Even nowadays, there is more data has been created in the past two years than in the entire previous history.
  14. EVOLVED TOOLS AND BIG DATA EMERGENCE The development stages of

    data processing gradually will be shifted from Labor to Machine
  15. DECISION SCIENCE How to accelerate powerful business decision, by having

    low risk and gain immense impacts both qual and quant [SIMPLIFY] DATA SCIENCE IN INDUSTRY 4.0 BUSINESS SCIENCE How to make a worthwhile business campaign, spend less money to get huge revenue [INTENSIFY] MARKETING SCIENCE How to accurately market a business product, with minimum cost use to attract potential loyal users [PERSONIFY]
  16. How to accelerate powerful business decision, by having low risk

    and gain immense impacts both qual and quant Decision Science
  17. DECISION SCIENCE: PRODUCT MONITORING Help non-technical users to recognize their

    own products by actionable insights and strategies. Products: Analytics Dashboard, Insight Visualization, Monitoring and Alerting System. PRODUCT MONITORING
  18. DECISION SCIENCE: MARKET PREDICTION Help non-technical users to predict accurately

    the next data pattern/behavior Products: Predictive Modeling, Dynamic Pricing, Time Series Forecasting MARKET PREDICTION
  19. DECISION SCIENCE: PRODUCT EXPERIMENTATION Help non-technical users to recklessly launch

    product to market, reduce the potential lost Products: A/B Testing, Sampling and Interview Analysis PRODUCT EXPERIMENTATION
  20. BUSINESS SCIENCE: FRAUD DETECTION Help non-technical users to find out

    fraudulent activities among the business. Products: Credit Scoring, Fraud Behavioral Analytics, User-based Segmentation FRAUD DETECTION
  21. BUSINESS SCIENCE: CHURN PREDICTION Help non-technical users to identify and

    prevent churn behavior of customers. Products: Churn Prediction Modeling, HR Attrition Dashboard CHURN PREDICTION
  22. BUSINESS SCIENCE: SOCIAL MEDIA ANALYTICS Help non-technical users to reveal

    social media trends for business strategy. Products: Sentiment Analysis, Product-Market-Fit Analysis, Social Engagement Dashboard SOCIAL MEDIA ANALYTICS
  23. How to flawlessly market a business product, with minimum cost

    use to attract potential loyal users Marketing Science
  24. MARKETING SCIENCE: CUSTOMER SEGMENTATION Help non-technical users to enhance product

    marketing to specific customer groups Products: RFM Analysis, Customer Segmentation Modeling CUSTOMER SEGMENTATION
  25. MARKETING SCIENCE: RECOMMENDER SYSTEM Help non-technical users to increase their

    sellings by recommend desired products Products: Content-based Filtering, Collaborative Filtering RECOMMENDER SYSTEM
  26. MARKETING SCIENCE: PRODUCT ADS Help non-technical users to create multi-channel

    and trustful ads to attract new customers Products: Targeted Ads, Omni-channel Dashboard PRODUCT ADS
  27. DATA SCIENCE SKILL SET REQUIREMENTS Ability to understand the business

    and data situation Ability to infer conclusion from data Ability to build system by programming 33.33% 33.33 % 33.33 % DOMAIN EXPERTISE ENGINEERING MATH / STAT
  28. RESEARCH Data Science works on data research: solving human problem

    VISIBLE Data has high visibility and prospective resource in the near future: Shape the Industry 4.0 CONCLUSIONS FLY Data talent is very demanding, your career could be skyrocketed
  29. CREDITS: This presentation template was created by Slidesgo, including icons

    by Flaticon, and infographics & images by Freepik THANKS! Do you have any questions? linkedin.com/in/fiqryrevadiansyah/ fi[email protected]