Challenges in Cloud Computing for Genomics

The video discusses the intersection of cloud computing and data analysis, focusing on processing large volumes of DNA sequences. It highlights the use of MapReduce technology, originally developed by Google, for handling massive data sets. The video also addresses technical challenges in cloud data storage, such as internet capacity limitations and practical solutions like physical data shipment. Privacy and security concerns are emphasized, particularly regarding genetic data, and potential solutions using encryption and authentication technologies are explored.

What is the primary focus of cloud computing in the context of data analysis?

• Developing new social media platforms

• Scanning large volumes of DNA sequences

• Improving video streaming quality

• Enhancing internet speed

Which company developed the MapReduce technology?

• Amazon

• Microsoft

• Facebook

• Google

What is a practical method mentioned for transferring large data sets to the cloud?

• Using high-speed internet

• Physical shipment of hard drives

• Uploading via mobile apps

• Streaming data continuously

What is the main technical barrier in cloud computing for genomic studies?

• Loading large volumes of data into the cloud

• High operational costs

• Inadequate software tools

• Lack of skilled personnel

Why is genetic data considered sensitive when stored in the cloud?

• It is expensive to store

• It requires constant updates

• It contains personal and familial information

• It is difficult to analyze

What is a major risk of centralizing genetic data in the cloud?

• Difficulty in data retrieval

• Increased data redundancy

• Higher storage costs

• Attractiveness as a target for breaches

What is a key challenge in storing data in the cloud?

• Limited storage capacity

• Lack of user-friendly interfaces

• Ensuring data privacy and security

• High energy consumption

How does decentralization of genetic data help in security?

• It localizes the impact of data breaches

• It reduces storage costs

• It speeds up data processing

• It simplifies data management

What technologies are essential for securing genetic data in the cloud?

• Data visualization tools

• Data compression and deduplication

• Encryption and authentication

• Machine learning algorithms

What is the importance of getting security right on the first try in cloud storage?

• To increase user engagement

• To lower maintenance costs

• To prevent accidental data exposure

• To reduce development time