For the first three attempts, don’t worry about the time limit.
ATTEMPT 1
The first time, aim for at least 40%. Look at the answers you got wrong and read the relevant sections in the chapter again to fix your learning gaps.
ATTEMPT 2
The second time, aim for at least 60%. Look at the answers you got wrong and read the relevant sections in the chapter again to fix any remaining learning gaps.
ATTEMPT 3
The third time, aim for at least 75%. Once you score 75% or more, you start working on your timing.
Tip
You may take more than three attempts to reach 75%. That’s okay. Just review the relevant sections in the chapter till you get there.
Target: Your aim is to keep the score the same while trying to answer these questions as quickly as possible. Here’s an example of how your next attempts should look like:
| Attempt | Score | Time Taken |
| Attempt 5 | 77% | 21 mins 30 seconds |
| Attempt 6 | 78% | 18 mins 34 seconds |
| Attempt 7 | 76% | 14 mins 44 seconds |
Table 2.2 – Sample timing practice drills on the online platform
Note
The time limits shown in the above table are just examples. Set your own time limits with each attempt based on the time limit of the quiz on the website.
With each new attempt, your score should stay above 75% while your “time taken” to complete should “decrease”. Repeat as many attempts as you want till you feel confident dealing with the time pressure.
In the previous chapter, you learned about several ways of storing data in AWS. In this chapter, you will explore the techniques for using that data and gaining some insight from the data. There are use cases where you have to process your data or load the data to a hive data warehouse to query and analyze the data. If you are on AWS and your data is in S3, then you have to create a table in hive on AWS EMR to query the data in the hive table. To provide the same functionality as a managed service, AWS has a product called Athena, where you create a data catalog and query your data on S3. If you need to transform the data, then AWS Glue is the best option to transform and restore it to S3. Imagine a use case where you need to stream data and create analytical reports on that data. For this, you can opt for AWS Kinesis Data Streams to stream data and store it in S3. Using Glue, the same data can be copied to Redshift for further analytical utilization. AWS Database Migration Service (DMS) provides seamless migration of heterogeneous and homogeneous databases. This chapter will cover the following topics that are required for the purpose of the certification:
Acedexam Training Policies
Learning resources
Other resources
Our Training Providers
