Your company is loading comma-separated values (CSV) files into Google BigQuery. The data is fully imported successfully; however, the imported data is not matching byte-to-byte to the source file.What is the most likely cause of this problem?
Answer(s): B
Your company produces 20,000 files every hour. Each data file is formatted as a comma separated values (CSV) file that is less than 4 KB. All files must be ingested on Google Cloud Platform before they can be processed. Your company site has a 200 ms latency to Google Cloud, and your Internet connection bandwidth is limited as 50 Mbps. You currently deploy a secure FTP (SFTP) server on a virtual machine in Google Compute Engine as the data ingestion point. A local SFTP client runs on a dedicated machine to transmit the CSV files as is. The goal is to make reports with data from the previous day available to the executives by 10:00 a.m. each day. This design is barely able to keep up with the current volume, even though the bandwidth utilization is rather low.You are told that due to seasonality, your company expects the number of files to double for the next three months. Which two actions should you take? (choose two.)
Answer(s): C,E
You are choosing a NoSQL database to handle telemetry data submitted from millions of Internet-of- Things (IoT) devices. The volume of data is growing at 100 TB per year, and each data entry has about 100 attributes. The data processing pipeline does not require atomicity, consistency, isolation, and durability (ACID). However, high availability and low latency are required.You need to analyze the data by querying against individual fields. Which three databases meet your requirements? (Choose three.)
Answer(s): B,D,F
Suppose you have a table that includes a nested column called "city" inside a column called "person", but when you try to submit the following query in BigQuery, it gives you an error.SELECT person FROM `project1.example.table1` WHERE city = "London"How would you correct the error?
Answer(s): A
To access the person.city column, you need to "UNNEST(person)" and JOIN it to table1 using a comma.
https://cloud.google.com/bigquery/docs/reference/standard-sql/migrating-from-legacy- sql#nested_repeated_results
What are two of the benefits of using denormalized data structures in BigQuery?
Denormalization increases query speed for tables with billions of rows because BigQuery's performance degrades when doing JOINs on large tables, but with a denormalized data structure, you don't have to use JOINs, since all of the data has been combined into one table. Denormalization also makes queries simpler because you do not have to use JOIN clauses.Denormalization increases the amount of data processed and the amount of storage required because it creates redundant data.
https://cloud.google.com/solutions/bigquery-data-warehouse#denormalizing_data
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question 59 - a newly-created role is not assigned to any user, nor granted to any other role. answer is b https://docs.snowflake.com/en/user-guide/security-access-control-overview
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answer to question 72 is d [sys_user_role]
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