Exam AWS Certified Data Engineer - Associate DEA-C01 topic 1 question 42 discussion

https://docs.aws.amazon.com/lake-formation/latest/dg/data-filters-about.html https://docs.aws.amazon.com/lake-formation/latest/dg/access-control-fine-grained.html

B: Since its a initial step for leverage fine grain control of Lakeformation. D: Give granular level control and meets the requirement

Registering the S3 path as an AWS Lake Formation location is the first step in leveraging Lake Formation's data governance and access control capabilities. This allows the data engineering team to centrally manage and govern the data stored in the S3 data lake. Enabling fine-grained access control in AWS Lake Formation and adding a data filter for each Region is the key step to achieve the desired access control. Data filters in Lake Formation allow you to define row-level and column-level access policies based on specific conditions or attributes, such as the Region in this case

If your table stored in an AWS Glue Data Catalog has tens and hundreds of thousands and millions of partitions, you can enable partition indexes on the table. With partition indexes, only the metadata for the partition value in the query’s filter is retrieved from the catalog instead of retrieving all the partitions’ metadata. The result is faster queries for such highly partitioned tables. The following table compares query runtimes between a partitioned table with no partition indexing and with partition indexing. The table contains approximately 100,000 partitions and uncompressed text data. The orders table is partitioned by the o_custkey column.

BD makes sense