JNTU B.Tech IV DATA ANALYTICS Previous Question Paper (July/August - 2022 - R16)

Primary data is original data collected specifically for a research purpose. The main sources include:

• Surveys and Questionnaires: Structured sets of questions distributed to a target population to gather quantitative or qualitative insights.
• Interviews: Direct, one-on-one interactions between the researcher and the respondent, allowing for in-depth exploration of opinions and experiences.
• Observations: Systematic recording of behaviors, events, or physical phenomena in their natural setting without direct interaction.
• Experiments: Controlled studies where independent variables are manipulated to observe the effect on dependent variables, establishing cause-and-effect relationships.
• Focus Groups: Group discussions moderated by a researcher to capture diverse perspectives and collective insights on a specific topic.

Exporting data to Amazon S3 involves moving local or on-premises datasets to a highly scalable object storage service. The process generally follows these steps:

1. Bucket Creation: Create an S3 bucket in the AWS Management Console, which acts as a container for objects.
2. Authentication: Configure AWS Identity and Access Management (IAM) credentials or roles to ensure secure access to the bucket.
3. Data Preparation: Organize and format data (e.g., CSV, JSON, Parquet) to ensure compatibility with downstream analytics services like Amazon Athena or Redshift.
4. Transfer Method Selection: Choose an appropriate transfer tool:
   • AWS CLI/SDK: Use the 'aws s3 cp' or 'sync' commands for programmatic or command-line uploads.
   • AWS DataSync: Automate and accelerate moving large volumes of data over the network.
   • AWS Snowball: For petabyte-scale data, use physical hardware devices to ship data directly to AWS.
5. Verification: Validate the integrity of the uploaded data using checksums or AWS S3 inventory reports to confirm successful transfer.