Intro to Big Data: Crash Course Statistics #38

CrashCourse
14 Nov 201811:22
EducationalLearning
32 Likes 10 Comments

TLDRThe video explores the emergence of "Big Data" - the vast amounts of digital information collected daily. It explains how data is gathered from numerous online and offline sources to profile users and target advertising. Potential benefits like personalized medicine are discussed, but privacy issues around this data collection are acknowledged. The sheer scale of data requires advanced systems, like those used by Netflix and Google Maps, to analyze it effectively. However, the complexity of Big Data presents problems that need addressing regarding privacy and responsible usage.

Takeaways
  • 😲 Big data refers to extremely large data sets that are difficult to process with traditional database tools.
  • 📈 The term "big data" became popular in the 1990s to describe the rapid growth of data being collected.
  • 📱 Smartphones, apps, social media and the internet of things are generating vast amounts of data every second.
  • 😎 Companies like Facebook, Google and Netflix use big data and algorithms to tailor ads, content and recommendations to individual users.
  • 🔍 Big data analysis has been used to predict personal traits and attributes from Facebook likes with a high degree of accuracy.
  • 👍🏻 Big data can have benefits like personalized medicine, improved entertainment recommendations and predicting which products people may want to buy.
  • 😕 However, the scale and complexity of big data raises privacy concerns over how much personal data is being collected and shared.
  • 🤖 In China, a big data system called City Brain is used to monitor traffic and direct emergency vehicles for faster response times.
  • 🎥 Netflix A/B tests different images for movie posters based on each user's viewing history data to optimize appeal.
  • 🌎 There are exciting possibilities for medicine, marketing and more, but also ethical challenges around privacy and security.
Q & A

  • What does the term 'Big Data' refer to?

    -The term 'Big Data' refers to extremely large and complex data sets that are difficult to process using traditional data processing tools and methods.

  • How did computers help with data collection and analysis?

    -Computers helped shorten the time it takes to collect, summarize and store data, allowing more data to be collected and analyzed than was previously possible.

  • How does Facebook categorize users?

    -Facebook sorts users into categories like political views, even if users don't explicitly state them. It infers views based on what pages a user's connections have liked.

  • How did Cambridge Analytica get data on millions of Facebook users?

    -Researcher Aleksandr Kogan used a quiz app to gather data on up to 87 million Facebook users. This data was then acquired by Cambridge Analytica.

  • How does Big Data help personalize medicine?

    -By sequencing an individual's genome, doctors can use Big Data to predict which medicines will have the fewest side effects or are least likely to interact with a patient's existing conditions.

  • How does Netflix use Big Data to make recommendations?

    -Netflix's algorithm learns from endless data on user clicks, watch time, likes/dislikes to find patterns and make recommendations. It also tests different images to see which ones users are most likely to click on.

  • How did Big Data help create new Coca-Cola products?

    -Coca-Cola analyzed data from their touchscreen soda fountains to see which flavor combinations were most popular. This data showed significant interest in Cherry Sprite, so they created it.

  • How does Google Maps use Big Data?

    -Google Maps uses real-time and historical location data from users to determine traffic conditions. They combine this with data from Waze on accidents and road issues.

  • What is City Brain and how does it use data?

    -City Brain is an AI system implemented in some cities to optimize traffic flow. It accesses data from government transportation departments, cameras, etc. to control signals and route emergency vehicles.

  • What are some privacy concerns with Big Data collection?

    -There are concerns about private companies having too much personal data about users that could be misused. There are also questions around informed consent and data security.

Outlines
00:00
📺 Introducing Big Data and Its Ubiquity

The paragraph introduces the concept of Big Data - extremely large data sets that are analyzed to reveal patterns and trends. It gives examples of how data is collected from everyday activities like using apps and buying items. The large volume of data from over 7 billion global internet users has given rise to the field of Big Data analytics.

05:01
🕵️‍♂️ Tracking User Data to Target Ads and Predict Personality

The paragraph explains how Big Data is used to target ads to users based on their online activity and demographics. It also summarizes a study that showed Facebook Likes can predict personality traits and attributes like intelligence, gender, and political affiliation to a high degree of accuracy.

10:06
👍 Benefits and Applications of Big Data Analytics

The paragraph highlights beneficial applications of Big Data like personalized medicine, sports recruiting, driverless vehicles, and traffic optimization in apps like Google Maps. It also introduces City Brain, an AI system in China that uses data to minimize traffic congestion in cities.

Mindmap
Keywords
💡Big Data
Big Data refers to extremely large and complex data sets that are difficult to process using traditional data processing tools and methods. In the video, big data is generated by everyday human activities like using apps and websites. Companies and governments collect this data for analysis and decision making. For example, Facebook uses big data to categorize users and target ads.
💡data collection
Data collection means gathering or recording information and measurements from different sources. The video gives examples like the US census, location tracking by phones, customer purchase records, etc. This exponentially growing collection of data has created the phenomenon of 'big data'.
💡data analysis
Data analysis refers to examining large data sets to uncover patterns, trends and insights that can inform decisions. The video shows how analysis of Facebook likes by Cambridge University revealed surprisingly personal user attributes. Companies like Netflix and Google also use big data analytics to improve their products and recommendations.
💡targeted advertising
Targeted advertising means showing customized ads to specific groups of customers based on analysis of their data and attributes. Facebook and Google allow advertisers to narrowly target ads using interests, demographics, behavior etc. derived from user data. The video raises concerns about misuse of targeted ads in political campaigns.
💡location tracking
Location tracking means tracing someone's location, often in real time, using GPS and other sensors on devices like smartphones. As discussed in the video, apps like Google Maps passively collect location data from users to display traffic information. City Brain takes this further by tracking locations to optimize transportation in cities.
💡algorithms
Algorithms refer to specific computational procedures that process input data and produce an output. The video explains how the Netflix algorithm analyzes user data to provide personalized recommendations on what shows to watch next. Similarly, Google Maps uses algorithms on location data to predict traffic conditions.
💡machine learning
Machine learning is an application of AI that allows systems to learn patterns from data in order to make decisions or predictions without explicit programming. While not directly referenced, machine learning enables many big data capabilities shown in the video - like image selection by Netflix and traffic prediction by Google Maps.
💡privacy
Privacy refers to the ability to keep personal information and data protected from unauthorized access or use. The video hints at growing privacy concerns related to big data collection by private companies and governments, which it promises to address in more depth in the next part.
💡targeted medicine
Targeted medicine refers to customizing medical treatments to a patient's genetic profile and health conditions. The video suggests big data analytics on patient genome sequencing could enable better predictions of suitable and effective medications on an individual basis.
💡automation
Automation denotes use of advanced technologies like AI and robotics to operate processes with minimal human intervention. The video cites automated traffic management by CityBrain and driverless cars as examples of big data enabling automation in transportation.
Highlights

The term “Big Data,” refers to data that is so large and complex that commonly used tools have trouble collecting, storing, and analyzing it.

By simply existing and using technology, each person generates large amounts of data on a daily basis.

The interconnected network of smart devices that collect data is sometimes called the “Internet of Things”, with items ranging from refrigerators to cars being connected.

Even something as simple as Facebook likes can reveal a surprising amount of information about a person when analyzed as part of Big Data.

Big Data allows advertisers to target very specific groups of people to receive customized ads.

Tools like Google Maps use the real-time location data from millions of users to predict traffic conditions.

In China, a system called City Brain uses traffic data and surveillance cameras to optimize routes and reduce congestion.

Netflix leverages user data to provide personalized recommendations for shows and movies.

The images Netflix displays for content are tailored to viewers based on their individual watching history.

In the future, Big Data could help further personalize medical treatments to an individual's genetic profile.

Big Data enables innovations like facial recognition software and optimized supply chains.

The massive amount of data being collected also raises privacy concerns that need to be addressed.

YouTube tracks metrics like how much of a video a user watched to understand engagement.

By simply watching this video, the viewer is generating data that YouTube stores and analyzes.

The scale and complexity of Big Data presents challenges alongside the innovations it enables.

Transcripts

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