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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. DECIPHER THE
    DISRUPTIVE
    INDUSTRY 4.0
    A Stellar Data Science Journey
    Wednesday, 5th of May 2021 | FMIPA UNTAN

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  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

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  3. 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

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  4. — W. Edwards Deming
    (Statistician, Professor, Author)
    “Without data, you're just
    another person with an opinion”

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  5. 01
    Unpredictable swift inside our solar
    system
    AGE OF
    DISRUPTION

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  6. 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

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  7. 175,000,000,000,000,
    000,000,000 MB*
    *Total Predicted Volume Data Stored in 2025: 175 Zettabytes
    *Seagate, 2021

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  8. 8+ TIMES
    Traveling Around Milky Way Galaxy*
    *Milky Way Galaxy distance: 100,000 light years

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  9. 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

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  10. TEXT DATA: HUMAN LANGUAGE
    Gmail text recommendation, suggest mail words
    along with correct the spellings.
    Technology: Natural Language Processing (NLP)
    TEXT RECOMMENDATION
    BERT ALGORITHM

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  11. 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

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  12. WHY AND HOW
    EVERYTHING
    HAPPENED?

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  13. 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

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  14. 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)

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  15. 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

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  16. 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

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  17. 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

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  18. 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

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  19. 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.

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  20. EVOLVED TOOLS AND BIG DATA EMERGENCE
    The development stages
    of data processing
    gradually will be shifted
    from Labor to Machine

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  21. 02
    What do we do to synthesize the
    world acceleration?
    OUR
    CONTRIBUTION

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  22. 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]

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  23. How to accelerate powerful
    business decision, by having low
    risk and gain immense impacts both
    qual and quant
    Decision Science

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  24. 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

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  25. 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

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  26. 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

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  27. How to make a worthwhile
    business campaign, spend less
    money to get huge revenue
    Business Science

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  28. 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

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  29. 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

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  30. 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

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  31. How to flawlessly market a
    business product, with minimum
    cost use to attract potential loyal
    users
    Marketing Science

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  32. MARKETING SCIENCE: CUSTOMER SEGMENTATION
    Help non-technical users to enhance product
    marketing to specific customer groups
    Products:
    RFM Analysis, Customer Segmentation Modeling
    CUSTOMER SEGMENTATION

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  33. MARKETING SCIENCE: RECOMMENDER SYSTEM
    Help non-technical users to increase their sellings
    by recommend desired products
    Products:
    Content-based Filtering, Collaborative Filtering
    RECOMMENDER SYSTEM

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  34. 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

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  35. 03
    Why Data Science is so demanding
    THE
    OPPORTUNITY

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  36. GARTNER: HYPE CYCLE IN DATA ANALYTICS

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  37. WEF: FUTURE OF JOB SURVEY 2020

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  38. 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

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  39. 04
    Conclusion of the whole talks
    END
    STATEMENT

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  40. 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

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  41. 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/
    [email protected]

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