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Big Data

Big Data

Year 13 Lesson


March 15, 2017

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  1. None
  2. What is Big Data? • Big Data is a term

    for large, complex and layered groups of data that can be analysed to spot patterns and trends. • Using data from multiple sources we can gain deeper and more accurate information that we can use to our benefit. • Big Data analysis requires multiple computers to work together as the amount of data collected is so large. • Much of the activity in our daily lives leaves behind a data footprint, such as searching online, using debit or credit cards, tracking a workout or even getting the bus. • This means Big Data is often available in real time – and in huge volumes. • Big Data analysis doesn’t tend to ask specific questions – it simply monitors information looking for trends or patterns.
  3. How Big is Big Data? • Adding up all the

    sources of data in the world, from the data collected by space exploration rovers to the latest social media posts - the numbers are staggering. • It’s estimated that we create over 2.5 trillion megabytes of data every day (that’s 2,500,000,000,000,000,000 bytes, or enough to fill 10 million blu-ray discs!) • By 2020, it is estimated that the digital universe will equal 40 zettabytes (40 billion terabytes, that’s around 5,247GB of machine-generated data for every person on the planet).
  4. Where does it come from? • In such a digitally

    connected world, any kind of digital interaction you can think of leaves behind a trail of data that gets collected and stored. • Big Data also comes from non-human sources, such as weather data and financial market information. • The apps you use on your phone, the time your train arrives (and when it leaves), how much you spend and what you spend it on. • All of this information (and much more) is collected and added to the ever-growing pool of Big Data to be interpreted.
  5. What do we do with it? • Businesses, governments, scientists

    and even the apps and services we use everyday already use Big Data, and new ways of using it are being explored all the time. • In the health industry, Big Data analytics helps decode complex DNA strings in minutes, and the data collected by smartphone health apps could help find links between lifestyle and illnesses. • Online shopping and social media data helps marketers deliver targeted offers and adverts. • Train companies use ticket data to map travel patterns and improve services.
  6. How is it changing the way we work? • Big

    Data is here to stay and it is already impacting everything from small startup businesses to international corporations. • Data is a valuable asset, leading to the rise of dedicated data departments. • Data analysis skills are set to become increasingly desirable to employers. • Big Data helps businesses find ways to be more efficient and target customers better. • Better business intelligence helps companies predict customer needs and market trends, leading to better customer experiences and more proactive customer service.
  7. What’s the future of Big Data? • There is no

    doubt Big Data will continue to grow, and the way we analyse it will have to evolve to keep up. With Big Data only getting bigger, companies who ignore it risk being left behind. • A Big Data buzzword to watch is ‘edge analytics’ - analysing data at the point it is collected (such as the sorting of CCTV images as they are captured into high and low priority). • Some experts predict Big Data may evolve into ‘fast’ or ‘actionable data’. This means companies should focus on making more of the data they have, whether it is ‘big’ or not.
  8. Getting the bus • Harry has been waiting at the

    bus stop for a while, so he opens a live bus times app on his phone to check when it will arrive. • What data does the app use to state when the bus will arrive?
  9. Getting the bus Bus speed The bus’s average speed measured

    by sensors or GPS Bus routes The planned bus route and distance between stops Weather data Real-time weather data Traffic data Crowd-sourced traffic data GPS on smartphonse Customer data Average passenger numbers from historical ticketing data
  10. Where does the data come from? Data server Your phone

  11. • The app tells Harry that the bus is four

    minutes away so he opens his music streaming app. After the first song he is played an advert for a local music festival. • What data does the app use to target the advert for the festival to Harry? The Festival
  12. The Festival Previous song choices Harry’s previous song choices Harry’s

    location Harry’s GPS location Friend’s events Events that his friends are attending (via social media) Social media profile Harry’s age and other statistics (via social media) Bands Harry follows Average passenger numbers from historical ticketing data
  13. • Harry likes what he hears and later buys a

    ticket online for himself and two friends. • That weekend they go to the festival and are impressed at how well organised the event is. • What Big Data sources do the festival organisers use to make their experience better? Tickets
  14. Tickets Crowd patterns Ticket sales and estimates help predict crowd

    patters so people can be kept safe Weather data Weather data is monitored to prepare the festival site Food and drink sales Food and drink sales tracked to minimise waste Social media feeds Average passenger numbers from Social media feeds are monitored and used to target future events
  15. Where does the data come from? Data server Festival planning