AWS Certified Data Analytics Test 2

You are building a Glue ETL job to extract the gaming data from your player data DynamoDB database and perform machine learning transformations on the data such as feature engineering. When defining your Glue ETL job properties, which worker type should you choose for your Glue data processing units (DPUs) so that you optimize cost while still delivering the correct type of processor for your workload?

Select 1 option(s):

Which AWS streaming service will meet your needs for ingesting the market data in the most efficient manner? (SELECT TWO)

Select 2 option(s):

Which data collection architecture best suits your real-time analytics requirements with the least amount of work on your part?

Select 1 option(s):

You have written a MapReduce job using Hive for which you wish to use all of your nodes in your EMR cluster to copy your DynamoDB table data into your HDFS. You wish to create your files on HDFS in the CSV format.
Which set of commands will execute this parallel copy for you?

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You have been given the requirements that the IoT data must be housed in your corporate data lake and that the data must be highly available. You have also been asked to transform the IoT data and group the data records into batches according to the literature’s published language. Your most important data collection system characteristics are durability of the data and data lake retrieval performance.
You have built a Kinesis Data Stream to collect the IoT data. Which of the following options will meet your requirements in the most cost optimized, durable, and performant manner?

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You have architected your current design of your mobile app to use REST APIs to communicate with your back-end storage solution. What set of AWS services will give you the low latency, high throughput, scalability, and durability you need to satisfy your requirements?

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The analytics visualizations require low latency data access that is 100% accurate. Data store response time is important. However, given the nature of the application, accuracy is your most important requirement, even if it means sacrificing response time.
You have built your data store for your blood analytics visualization solution with DynamoDB as your data store. However, on occasion your visualizations show inaccurate data for your medical condition statistical charts. What might be the root cause of this?

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Your team lead has decided to use DynamoDB for your data store based on its consistent single-digit millisecond latency. Given your unique requirements, which technique allows you to reach the maximum DynamoDB performance?

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What data collection and storage solution best meets your requirements?

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Your data used to augment the machine learning inferences needs to be stored in a data storage solution that has the following freshness characteristics:
It needs to be optimized for storing key/value pairs and as a document store.
It needs to perform at the highest request rate you can provide.
It needs to perform at very low latency.
It needs to be able to store petabytes of data.
You need to optimize for cost.
You need to run your data analytics application from within your VPC.
Your solution needs to be highly available, therefore you have a data store requirement of availability across 3 availability zones.
Which database solution matches the freshness requirements of your data?

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You have been asked to optimize for cost and for microsecond response times for your operational queries of your data store. Which set of AWS services satisfy your requirements?

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What option best describes the operational characteristics of the solution that best meets your requirements in the most efficient manner?

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You have started building your data warehouse in Redshift. You have used the default settings when creating your tables in Redshift. When you start using your new data warehouse, you notice that queries against certain tables are slower than expected when the queries are built so that they use restrictive predicates on secondary sort columns, without using the primary columns. However, your queries that use group by and order by operations run very quickly.
What might be the root of your slow performance?

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You have created a Kinesis Data Firehose stream to stream your IoT data to one of your S3 buckets. You now need to use a metadata cataloging service to build your persistent metadata store. Which option fits your data processing requirements?

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You plan to use Amazon QuickSight as your data visualization tool. If you are building a visualization that includes 20 date fields, 35 integer fields, and 10 string fields of length 100, what SPICE capacity allocation do you need to have available in your QuickSight account to accommodate your approximately 18 million citizen records?

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Unfortunately, your current solution, depicted in the diagram below, is prone to failures and is not easily scaled. You also have a difficult optimizing the costs of your SaaS offering because you are using sunk costs (the physical servers). You have been tasked with modernizing your analytics solution.

Which option provides the most cost effective, performant, and scalable solution?

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You have built a collection system as follows: a Kinesis Producer Library application that writes records to your Kinesis Data Streams stream shards. You have configured your Kinesis Producer constructor as follows:
RecordMaxBufferedTime = 200
MaxConnections = 2
RequestTimeout = 5000
Region = us-east-1
Your Kinesis Data Streams writes to Kinesis Data Firehose. Kinesis Data Firehose uses a Lambda function to transform your data into the Avro format before writing it to your S3 bucket in your data lake.
You have noticed that your data collection pipeline is not performing as well as you had expected. What may be the cause, and what can you do to improve the situation?

Select 1 option(s):

You have constructed a Kinesis Data Streams infrastructure with KPL producer applications delivering the transportation data into your Kinesis shards. You are in the process of building your Kinesis Consumer Library application code to consume the streaming data from Kinesis and write the data to your S3 buckets. What happens when your KCL worker code fails in the middle of retrieving a record from your Kinesis stream?

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You have been tasked with collecting the sports data from your 100+ websites in real-time, process it, and then store it in your S3 data lake. You also need to store the raw data you receive in a separate S3 prefix so that the raw data can be used by other analytics applications in the future.
Which of the following options is the most cost effective and simplest to implement that addresses your requirements?

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You have constructed a Kinesis Data Firehose data collection pipeline to gather the data. You now wish to store the data in a DynamoDB database for access via REST APIs by your real estate agents out in the field using their mobile devices. You have implemented the REST APIs using API Gateway.
When you run your first canary deployment of your Lambda function you notice that your Lambda function attempts to process your buffered Kinesis records 3 times and then skips the batch of records. What might be the cause of the problem, and how can you correct the issue?

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With this latest version of your software you have decided to use DynamoDB global tables to make your application data available across your distribution as a multi-master, multi-region database. You have transactional operations within your application code base that require atomicity, consistency, isolation, and durability (ACID) capabilities.
You have deployed your DynamoDB global tables in your three regions but you are now noticing that when you issue a TransactWriteItems operation in one region you see partially completed transactions for a period of time in the other two regions. Why is this, and what can you do to remediate the situation?

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Your data collection system will need to stream the social media and web site comments in real-time to your data store. Your management team wishes to use the data in the data store to perform ad-hoc analysis of the customer feedback in real-time. Which option gives you the most cost efficient and performant solution?

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Which option meets your requirements and gives you the most cost efficient solution to your design problem?

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As you create your DynamoDB table for your political election polling data store you need to select a partition key and a sort key, since you wish to use a composite key to improve performance and DynamoDB capacity management. You have several choices for your political election polling partition/sort key combination. Your researchers need to produce several visualizations of the data to understand the distribution of votes by age, nationality, political party affiliation, selected candidate, etc. An example would be to visualize votes collected for a particular candidate by age group and by voter nationality.

Which option will give you the best performance for your political election polling table?

Select 1 option(s):

One of your partners needs you to transform industry data that is sourced in the JSON format so that the data can be used by their machine learning model in the CSV format. You have chosen AWS Glue as your transformation tool. One particular requirement is that your ETL script needs to convert a composite JSON format of, for example {“id”: 1435678, “product name”: “product A”, “product cost”: 54.23}, to values in your CSV file of int, string, and double.
Which option leverages AWS Glue to perform the required JSON transformation in the most cost effective optimal manner?

Select 1 option(s):

Which of the following steps are NOT required when moving your data from your EMR cluster to your Redshift cluster? (SELECT TWO)

Select 2 option(s):

You have loaded your initial retail store data into your Redshift cluster using the COPY command to copy the data from your S3 data lake. For the last several weeks you have been streaming the retail store data into your Redshift tables. You are now noticing that your queries from your Redshift tables are taking longer to execute. Which of the following options will correct your performance problem?

Select 1 option(s):

You need to build an EMR cluster to store and process this streaming data to prepare it for use in your machine learning analytics applications. Based on your streaming data activity volume you estimate that your cluster will need to have more than 50 nodes.
Based on your streaming data volume and your machine learning based use cases, which types of EC2 instances should you use for your master node and core/task nodes?

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Based on the schedule of sporting events and the popularity of some events, such as the Fédération Internationale de Football Association (FIFA) football world cup, you need to be able to scale your EMR cluster EC2 instances in or out depending on the particular demand for analytics for the given event. Your goal is to provide adequate performance for the given workload while also maintaining the most cost effective environment over time.
Which type of scaling plan should you use for your EMR cluster?

Select 1 option(s):

What combination of AWS services and tasks implement your required visualization solution in the most cost effective manner?

Select 1 option(s):

Which option gives you the most cost effective solution to your data analysis visualization problem?

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You also need to provide the capability to perform ad-hoc queries of your accumulated streamed data to your management team. Which option gives you the most cost effective and performant solution for your ad-hoc query needs?

Select 1 option(s):

Which set of AWS services allow you to build visualizations of your IoT data in the most expeditious, cost effective manner?

Select 1 option(s):

How will you grant permissions to your Glue crawler to access your encrypted S3 buckets?

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Which option is the best practice when configuring EMR device volumes using the EMR security configuration?

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Which option depicts the best measures you can take to secure your EMR clusters and the other AWS services used in your data collection/analytics pipeline are as isolated from outside influence as possible?

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Your AWS Config rules for your S3 buckets in your data lake should send you notifications whenever an S3 bucket is created, modified, or deleted. However, you are not receiving these notifications when your S3 resources change. What might be the cause of this problem?

Select 1 option(s):

Because of the very large number of records produced by your KPL applications, you have decided to use KPL aggregation. Also, your KCL record processing code relies on unique identifiers for the processing of your KPL user records. What attribute of your streamed records can you use as your unique identifier for your KPL user records after de-aggregating the Kinesis Data Stream record?

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Your team is responsible for gathering this sensor data into a data warehouse for use in analytics apps used by your data scientists to gain insights into the efficiency of their airline fleet. Which of the following options is the simplest and most cost effective method of getting the airline data into your data warehouse?

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You are streaming your game data through a Kinesis Data stream with the Kinesis Producer Library (KPL) aggregating your user records. Your management team has stressed that real-time recommendations need to be as fast as possible. Which option gives you the best consumer application deaggregation method to retrieve your user records?

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You have built a data collection system that is based on Kinesis Data Streams feeding Kinesis Data Firehose which then loads your data into your Redshift data warehouse. During testing of your data collection system you have noticed that your data is not being delivered into your Redshift cluster. Which of the following should you NOT check when trying to determine the problem?

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You have built a data collection system that uses Kinesis Data Streams to feed a Kinesis Data Firehose stream. You want to configure the Firehose stream to leverage Lambda to transform your data and then write your data to your Elasticsearch cluster so that you can provide a cached data search capability for your SaaS offering.
When you conduct your first tests you find that your streaming data is not being delivered to your Elasticsearch domain. What may be the root of the problem?

Select 1 option(s):

Your data collection solution looks like this: VPC Flow logs are sent to CloudWatch. The CloudWatch data is streamed through Kinesis Data Firehose which leverages Lambda to decompress the log data and finally sends the decompressed log data to Splunk for analytics and monitoring.
How can you most efficiently use metadata in your existing stream records to categorize the stream records by account owner, VPC, and service used?

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You have chosen to populate your data lake via a data collection system that uses Kinesis Data Streams to capture the data records from a producer application. You have the requirement to keep the data records in sequence order so that your analytics applications can infer when users take a sequence of actions, such as selecting a song to play and then either skipping the song or marking the song as a favorite.
As you start to test your data collection pipeline you notice that some of your data records arrive out of sequence. Which option can help you correct this problem?

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You have decided to use the Redshift automatic compression feature to accomplish your data compression in your warehouse. Which of the following options is NOT one of the operations performed by automatic compression when loading your data into your Redshift tables using the COPY command?

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You have loaded all of your data into your Redshift data warehouse and have started to create the business intelligence analytics views for your management team. However, your queries are not performing as well as they should. The response time for producing analytics insights is slow. You have decided to leverage column compression on your Redshift tables to improve query performance. How would you apply compression to your customer table in Redshift?

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You have chosen Redshift as your data warehouse technology. You are now configuring your snapshot schedule for your primary tables. Which of the following options defines your snapshot schedule to occur every day of the week starting at 12:30 AM on a 1 hour increment?

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You are designing your Redshift data warehouse cluster and you need to construct your basic queries for extracting your data for your analytics applications. Because of the large amount of data stored in your warehouse you want to use distributed queries across your warehouse compute nodes to improve performance (see the diagram below).

Which option represents an example query you would run on your compute nodes?

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You need your metastore for your EMR cluster to be persistent. Based on your requirements, which option gives you the best metastore option with the least amount of effort?

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You have a data collection pipeline that loads building data from your various data sources (data warehouses, relational databases, etc.) into your data lake on S3. You are creating these visualizations in QuickSight. Several of your data files arrive on your S3 buckets in the gzip compressed format, while others are in the XLSX and TSV formats. How can you prepare these source data files for use as data sources in your QuickSight visualizations?

Select 1 option(s):