Webinar - Data Science Role in Industry 4.0

Transcript

1. DECIPHER THE DISRUPTIVE INDUSTRY 4.0 A Stellar Data Science Journey Wednesday, 5th of May 2021 | FMIPA UNTAN
2. 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
3. DISCLAIMER
4. 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
5. — W. Edwards Deming (Statistician, Professor, Author) “Without data, you're just another person with an opinion”
6. 01 Unpredictable swift inside our solar system AGE OF DISRUPTION
7. 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
8. 175,000,000,000,000, 000,000,000 MB* *Total Predicted Volume Data Stored in 2025: 175 Zettabytes *Seagate, 2021
9. 8+ TIMES Traveling Around Milky Way Galaxy* *Milky Way Galaxy distance: 100,000 light years
10. 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
11. TEXT DATA: HUMAN LANGUAGE Gmail text recommendation, suggest mail words along with correct the spellings. Technology: Natural Language Processing (NLP) TEXT RECOMMENDATION BERT ALGORITHM
12. 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
13. WHY AND HOW EVERYTHING HAPPENED?
14. 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
15. 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)
16. 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
17. 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
18. 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
19. 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
20. 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.
21. EVOLVED TOOLS AND BIG DATA EMERGENCE The development stages of data processing gradually will be shifted from Labor to Machine
22. 02 What do we do to synthesize the world acceleration? OUR CONTRIBUTION
23. 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]
24. How to accelerate powerful business decision, by having low risk and gain immense impacts both qual and quant Decision Science
25. 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
26. 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
27. 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
28. How to make a worthwhile business campaign, spend less money to get huge revenue Business Science
29. 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
30. 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
31. 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
32. How to flawlessly market a business product, with minimum cost use to attract potential loyal users Marketing Science
33. MARKETING SCIENCE: CUSTOMER SEGMENTATION Help non-technical users to enhance product marketing to specific customer groups Products: RFM Analysis, Customer Segmentation Modeling CUSTOMER SEGMENTATION
34. MARKETING SCIENCE: RECOMMENDER SYSTEM Help non-technical users to increase their sellings by recommend desired products Products: Content-based Filtering, Collaborative Filtering RECOMMENDER SYSTEM
35. 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
36. 03 Why Data Science is so demanding THE OPPORTUNITY
37. GARTNER: HYPE CYCLE IN DATA ANALYTICS
38. WEF: FUTURE OF JOB SURVEY 2020
39. 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
40. 04 Conclusion of the whole talks END STATEMENT
41. 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
42. 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/ fiqry.revadiansyah@accenture.com