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NEW QUESTION: 1
Which one of the following best describes the correct order of the settlements process?
A. trade entry, confirmation, settlement, nostro reconciliation, netting
B. trade entry, confirmation, netting, settlement, nostro reconciliation
C. confirmation, netting, trade entry, settlement, nostro reconciliation
D. netting, trade entry, settlement, confirmation, nostro reconciliation
Answer: B
NEW QUESTION: 2
A. Option C
B. Option D
C. Option A
D. Option B
Answer: D
NEW QUESTION: 3
A global shoemaker has over a thousand retail stores which they manage themselves, sell through brokers in other discounted stores, and they also sell online. These channels are completely independent. There is no system that merges these data sets together to allow the COO to have comprehensive insight. You need to provide a company-wide picture of its channels and be enabled to do ad-hoc analytics when required. How can you configure this? Choose two.
Choose the 2 correct answers:
A. Use Amazon Redshift to load, sort, distribute, and compress the data into its tables so that analytical queries can execute efficiently and in parallel. Lastly, for visualizing the analytics, Amazon QuickSight can be used, or one of the many partner visualization platforms via the OBDC/JDBC connection to Amazon Redshift.
B. Use Amazon EMR to load, sort, distribute, and compress the data into its tables so that analytical queries can execute efficiently and in parallel. Lastly, for visualizing the analytics, Amazon QuickSight can be used, or one of the many partner visualization platforms via the OBDC/JDBC connection to Amazon EMR.
C. First, get all the data from the many different sources onto Amazon S3. Then, Amazon EMR is used to transform and cleanse the data from the source format into the destination and desired format.
D. First, get all the data from the many different sources onto Amazon DynamoDB. Then, Amazon Redshift is used to transform and cleanse the data from the source format into the destination and a format.
Answer: A,C
Explanation:
An enterprise data warehouse is a terrific way to solve this problem. The data warehouse needs to collect data from each of the three channels'various systems and from public records for weather and economic data. Each data source sends data daily for consumption by the data warehouse. Because each data source may be structured differently, an extract, transform, and load (ETL) process is performed to reformat the data into a common structure. Then, analytics can be performed across data from all sources simultaneously Reference:
https://d0.awsstatic.com/whitepapers/Big_Data_Analytics_Options_on_AWS.pdf
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