Power of Big Data!

00:02:42
https://www.youtube.com/watch?v=m5Iij3zQp_w

Resumen

TLDRAt Walmart, large-scale data analytics play a crucial role in enhancing business efficiency and customer satisfaction. With over 11,000 stores worldwide and immense data processing capabilities, the analytics team focuses on extracting valuable insights from various internal and external data sets. Utilizing advanced statistical methods and machine learning algorithms, they work on predictive models to forecast demand, manage inventory, and determine the best locations for new stores. This data-driven approach empowers Walmart to optimize product assortments, understand customer demographics, and maintain its competitive edge in the retail industry while fulfilling its commitment to providing affordable options to its customers.

Para llevar

  • 📊 Walmart has the second-largest in-memory platform globally.
  • 🌍 Operates over 11,000 stores across 27 countries.
  • 💥 Processes 250 million transactions weekly.
  • 📈 Integrates 200 internal and external data sets.
  • 🧠 Uses advanced statistics and machine learning.
  • 📉 Applies regression models for demand forecasting.
  • 🏬 Utilizes demographic data for store location analysis.
  • 📱 Offers mobile applications for competitive advantage.
  • 💪 Aims to keep customer promise of saving money.
  • 🤝 Collaborates with top data analytics PhDs.

Cronología

  • 00:00:00 - 00:02:42

    The speaker joined Walmart due to its significant data capabilities, including the second-largest in-memory platform globally. They discussed the vast amounts of data handled, including 40 petabytes and 250 million transactions weekly, to assist business partners in making informed decisions. The integration of data analytics into various processes, such as merchandising and customer segmentation, is emphasized. The team collaborates with PhD data analysts to merge around 200 data sets into a comprehensive platform, utilizing advanced statistical methods and machine learning algorithms, like regression and clustering. These analytics help in predicting sales, assessing demand, and determining optimal store locations based on various demographic factors, enabling Walmart to maintain its competitive position while ensuring customer satisfaction by saving money and improving lives.

Mapa mental

Vídeo de preguntas y respuestas

  • Why did the speaker join Walmart?

    The speaker joined Walmart because of the impressive in-memory platform and the opportunity to work with big data analytics.

  • How much data does Walmart handle?

    Walmart handles 40 petabytes of data.

  • What types of algorithms do they use for predictions?

    They use regression models, elastic net, and clustering algorithms like support vector machines.

  • What is the goal of Walmart's data analytics team?

    The goal is to analyze data to help make informed decisions, predict sales, and reduce costs.

  • How does Walmart use this data?

    Walmart uses data to understand customer needs and to improve their offerings, ensuring they deliver on their promise to save money and enhance quality of life.

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  • 00:00:05
    one of the reasons I joined Walmart is
  • 00:00:07
    because we have the second-largest in
  • 00:00:10
    memory platform in the whole world and
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    the application that we are working on
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    it mines through billions of rows of
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    data to get valuable information out of
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    this big data that our business partners
  • 00:00:20
    can use to make better informed
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    decisions we have over 11,000 stores in
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    27 countries we have 11 ecommerce sites
  • 00:00:29
    we have 40 petabytes of data we do 250
  • 00:00:33
    million transactions a week on a global
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    scale we are infusing data analytics
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    into every process from merchandising to
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    assortment and even to customer
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    segmentations we are developing
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    applications that think exactly like our
  • 00:00:50
    stakeholders as part of the big data
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    analytics team here at Walmart I get to
  • 00:00:55
    work with data analytics phd's every day
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    and we have built a solution where we
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    take in almost 200 internal and external
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    big data sets and we integrate all of
  • 00:01:05
    that into one big comprehensive data
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    platform and we run all our analytic
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    solutions on top of that it's amazing to
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    work in an environment where you're
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    exposed not only to advanced statistic
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    math that we're doing here but even to
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    machine learning algorithms I'm
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    referring to last model that were using
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    daily to reach regression and elastic
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    net based on some of the variables that
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    we pick from whether for example economy
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    competitors social events we create
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    thousands of possible candidates
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    variables that will enable us in our
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    algorithms to predict the cells and
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    demand and reduce the cost for the
  • 00:01:48
    company we're using clustering
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    algorithms like support vector machines
  • 00:01:53
    to predict the first year demand and
  • 00:01:55
    write assortment of products of yet to
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    be open stores based on things like
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    demographics weather patterns income
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    population density and location in the
  • 00:02:04
    Saran
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    this information will help us determine
  • 00:02:07
    potential story locations that will
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    provide our customers convenient access
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    for the things they need we have a great
  • 00:02:13
    community of developers here we're able
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    to use modern open source software and
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    work on mobile applications to give us
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    that competitive advantage so we can
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    remain the world's number one company
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    all of this data allows us to analyze
  • 00:02:27
    our customers analyze what they need so
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    we can keep that promise to them to save
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    money and live better
Etiquetas
  • Walmart
  • Big Data
  • Data Analytics
  • Machine Learning
  • Predictive Modeling
  • Customer Insights
  • E-commerce
  • Retail
  • Statistical Methods
  • Data Integration