Learn about the current technology horizon for big data, as well as the challenges in choosing technologies for architectures.
- [Instructor] What technologies and products…are available today to build big data applications?…I just did a Google search for big data technologies.…Look at these results.…What you immediately see is that there are…too many options available to you…for each of the modules you want to build.…Actually, too many for my liking.…Why?…First, the technologies are not mature.…There are many open-source projects that have come up…in the last five years to solve specific big data needs.…
Too many start-ups are now building new products…or support open-source initiatives.…The technologies are evolving very rapidly.…If you build your application…with the current version of this software,…you will see that the next version of the software…drastically changes functionality…even breaking backward compatibility.…While the products offer ground-breaking functionality,…they lack usability, maintainability,…serviceability, and developer support.…
Those features will come in eventually…but we don't know which of the current technology options…
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 data acquisition, transport, processing, storage, and service. 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: archiving audit logs and performing customer analytics
- Technology options
- Designing solutions
- Best practices
Skill Level Advanced
Big Data Foundations: Program Managementwith Alan Simon1h 11m Intermediate
1. Intro to Big Data Applications
2. Use Case 1: Data Warehouse (DW)
3. Use Case 2: Log Accumulation (LA)
4. Use Case 3: IT Operations Analytics (OA)
5. Use Case 4: Customer 360 (C360)
6. Use Case 5: Customer Analytics (CA)
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