Build an Apache Spark™ application to address a real business problem or core business concern related to customer care, marketing, risk management, or operations.
We live in a data-driven world. As a developer, data engineer, or data scientist, you need the right tools to access, and analyze data to generate usable insights to meet business requirements.
Enter Apache Spark. Spark is a powerful open-source data analytics tool built for cluster-computing. It has quickly gained popularity because of its speed, iterative computing capabilities, and better data access with memory caching. Spark has enabled Uber, Pinterest, Conviva, and Yahoo! to quickly analyze their massive data sets and adapt their operations. We know that’s just the tip of the iceberg, which is why IBM is launching the Apache Spark Makers Build competition, an online hackathon focused on building Apache Spark analyses and applications to address real business problems related to customer care, marketing, risk management, or operations.
We’re inviting software developers, data scientists, and data engineers do more with Spark – to move past experimental hacks and create business assets that have value for both technical and non-technical end users.
This challenge is open in the following jurisdictions only: USA, Canada (with exception of Quebec province), Hong Kong, China, Mexico, Germany, Japan, India, Israel, South Korea, United Kingdom, Australia, Netherlands, and France.
Entrants in these areas may compete if they are:
- Individuals/Teams of Individuals - Minimum Age: 18
- Companies with 50 or fewer employees are eligible for cash prizes
- Large Organizations with more than 50 employees (eligible for Large Organization Recognition Award only – not cash prizes)
Note that government-owned entities and employees or contractors currently employed by IBM or Devpost are not eligible for any prize.
Software partners and those receiving funding or assistance from IBM for application development are not eligible. Any application that is or was funded or compensated, partially or fully, by IBM for its development is not eligible for entry.
Main Requirement: Bring Apache Spark to the business. Build an Apache Spark application to address a real business problem or core business concern related to customer care, marketing, risk management, or operations. Your Apache Spark application should be something that business stakeholders could use and deploy in the future.
To meet the minimum eligibility requirements you must:
- Identify a business need that could be informed by data analysis (see examples).
- Find data (publicly available data or data from your own business) to analyze using Apache Spark to inform that business need.
- Analyze the data using Apache Spark and share your analysis code for judging (via adding a GitHub link or privately shared file to your submission). (Note: Spark applications are encouraged – though not required – to be portable, with the ability to run on different cloud platforms.)
- Showcase your analysis output by including the following in your submission:
- a visual (graphic) or textual explanation of your results; and
- a video demo explaining your process and outcomes.
- (Pro tip: we recommend explaining how your entry meets the judging criteria in your video demo or text description, such as the portability of your Spark application.)
- OPTIONAL: You may develop a working front-end smartphone or web application that utilizes your Spark-analyzed data app to help solve a business need, but this is not required to be eligible for a prize. If you build a front-end smartphone or web application here's how to share it with us for judging and testing.
New/Existing Applications: Both new and existing applications may be submitted. However, for existing applications, submitters must identify and explain the updates made during the submission period.
Data Scientist, Tesla
Director of Content Science & Algorithms , Netflix
Founder & CTO, Silicon Valley Data Science
Vice President, Offering Management, IBM Analytics
Director Special Projects, Galvanize
CTO, 4Quant Ltd & Lecturer, ETH Zurich
Usability potential in a business setting for both technical and non-technical end users with diverse backgrounds.
Cognitive capabilities invoking machine learning or advanced analytics techniques. Is the data analysis accessible via a web or mobile app, or is it a machine-learning algorithm?
Stability & Scalability
Stability potential of data analysis or application and scalability to reach multiple end users. Can more than twenty users access and run the app concurrently?
Market Readiness & Portability of Spark Application
Includes the extent to which your Spark app has moved past the proof of concept stage, as well as the ease in which it can be deployed on multiple cloud platforms such as private cloud or IBM Bluemix.