Big Data Challenge
EDU

The Big Data Challege is a fun, student-vs-student big data challenge designed for high school and college students, and the most fun way to introduce your students to this growing industry.

Your students can participate in a Big Data Challenge as part of an in-person or Virtual CodeDay, or we can host a Big Data Challenge in your classroom!

During the challenge, students will learn about Big Data and the HPCC/ECL programming system in the education module, and then participate in a team-vs-team challenge.

We will work with you to schedule a time for your challenge, and provide you with the materials you need to run your challenge, including an online IDE with cloud computing resources. You also have the option to request big data mentors from our partner, LexisNexis Risk Solutions.

You will need to set aside the following class time:

  • Education module: 30 minutes
  • Challenge: >30 minutes (we recommend 60-90 minutes)

Challenge Details

The challenge period starts after you've completed a brief education module. It can be as long as you'd like, but we recommend you allocate 45min to 1hr, or a roughly a class period.

During the challenge period, students will log into an online IDE and compute cluster to run their code. (No installs needed!) When logging in, students will see a loaded dataset, and a list of questions about that dataset. Each question has a point value, and more difficult questions are worth more points.

Teams compete to get the most points by answering questions before the time limit. Teachers will need to verify the solution using our answer guide.

Education Module

Before the big data challenge starts, we recommend you host our learning module, which gets students up-to-speed on what they need to know about big data. You can play a video about the learning module, or run the learning module yourself.

You can view an example of the full learning module, including interaction points, below.

The learning module is divided into two parts:

  • History and Background of Big Data
    • What does "big data" mean?
    • Why does big data need special processing vs regular data?
    • What are the components of a big data system, and how do they work together?
    • What are some real-world applications of big data?
    • What careers are available in Big Data?
  • Big Data Coding using the ECL Programming Language
    • ECL syntax, and how it compares to other programming languages.
    • Defining data structure and loading data.
    • Filtering, sorting, and aggregating data.
    • Writing custom transforms.
    • Table joins.
    • Visualizations.

Students are not expected to remember all the information from the education module. The slide deck is full of examples, and is available as a reference source during the challenge.

Teacher Resources

Next Steps

Contact us to get started. We'll need:

  • an estimate of the number of students participating
  • approximate date you'd like to run your challenge
  • how you'd like to teach the learning module
  • whether you're requesting a big data mentor from our partner company, LexisNexis Risk Solutions

Eligibility

Prerequisites

To participate in a Big Data Challenge, students should:

  • Be proficient in at least one text-based programming language, such as Java or Python.
  • Be comfortable with referencing technical documentation (cheat-sheets and presentations).
  • Be fluent in English (documentation is currently only available in English).
  • Experience with databases or SQL is a plus, but NOT required.

For fairness, it's best if all participating students have a similar skill level. We can run multiple challenges for different classes if needed.

Technical Requirements

To access the website, students must:

  • Use a desktop, laptop, or Chromebook. Tablets and phones are not supported. (One computer can be shared by multiple students via the "pair programming" model.)
  • Have reliable internet access
  • Be using a version of the Firefox, Chrome, or Safari released within the last year.

Presented in partnership with

LexisNexis Risk Solutions

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