Learn about some best practices while building data storage modules within the big data architecture.
- [Instructor] We will now review some of the best practices…for big data storage.…The first best practice is to choose horses for courses.…As an architect, you will be tempted as well as pressured…into using a single database product…for your entire business.…A single product minimizes cost and effort…for the business to buy and maintain,…but the scalability needed for big data…demands that we use products…that are best of breed for different use cases…or even within the same use case.…
Look for keeping the schema flexible.…Changing schema on an existing large database…is time and effort consuming.…Do you need backups for the data?…Having products that replicate data across nodes…help you avoid backups.…Also, the same data is stored in detail and summary forms…in different databases.…Do you need backups for both?…You want to make a decision on this…based on your business needs.…
Transactions are an important concept…in working with databases, but with big data,…the level of transaction support…varies between different products.…
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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