Discuss some key design issues and recommendations for the individual components within the mobile couponing use case.
- [Instructor] Let us now deep dive…into some key elements…of the mobile couponing architecture.…The reference databases…for the predictions, namely user preferences…and location services…should be designed in specific ways…to enable fast querying and caching.…First, let us look at the user preferences table.…It is indexed by the mobile phone number…and contains information…about the type and sub type of service…and a score to indicate user affinity.…
For example, service type would be food.…Service sub type would be Italian food…and the user affinity or preference…for this type of food will be a score of seven…out of 10 points.…The location services database…will be indexed by the location ID.…The location ID might be just geographical coordinates.…It again contains type and sub type for service,…the actual business name…and details of the coupons,…so when the location and mobile number information…comes in, we use the mobile number…to query user preferences,…then we query the location services,…we then match them both based on the service type…
There is no coding involved. Instead you will see how big data tools can help solve some of the most complex challenges for businesses that generate, store, and analyze large amounts of data. The use cases are drawn from a variety of industries, including ecommerce and IT. Instructor Kumaran Ponnambalam shows how to analyze a problem, draw an architectural outline, choose the right technologies, and finalize the solution. After each use case, he reviews related best practices for real-time streaming, predictive analytics, parallel processing, and pipeline management. Each lesson is rich in practical techniques and insights from a developer who has experienced the benefits and shortcomings of these technologies firsthand.
- Components of a big data application
- Big data app development strategies
- Use cases: fraud detection and product recommendations
- Technology options
- Designing solutions
- Best practices