In many cases, customers might not know the implications of the 9s with respect to scheduled maintenance, upgrades, etc. It's possible that they are holding unnecessary expectations that significantly exceed their requirements.
-> Even though 0.0009 % increase it looks like a small increment, an addition of a single 9 reduces the possible downtime by 10 times. So the effort is often much greater.
Reference link- https://en.wikipedia.org/wiki/High_availability

Reference:

Explanation
Option A is Correct- BigQuery Flex Slots for cyclical workloads that require extra capacity, or for workloads that need to process a lot of data in a short time, and so would be less expensive to run using reserved slots for a short time.

Explanation
Google Cloud commitment to keep the data secure and private:
1. Org owns the data and not Google
2. Google does not sell data to 3rd parties
3. All customer data is encrypted by default
4. Google Cloud guards insider against your data
5. No backdoor access to any govt. entity
6. Google's privacy practices are audited against international standards

Reference:
Cloud Bigtable is a sparsely populated table that can scale to billions of rows and thousands of columns, enabling you to store terabytes or even petabytes of data. A single value in each row is indexed; this value is known as the row key. Bigtable is ideal for storing very large amounts of single-keyed data with very low latency. It supports high read and write throughput at low latency, and it is an ideal data source for MapReduce operations.
Bigtable is exposed to applications through multiple client libraries, including a supported extension to the Apache HBase library for Java. As a result, it integrates with the existing Apache ecosystem of open-source Big Data software.
Bigtable's powerful back-end servers offer several key advantages over a self-managed HBase installation:
Incredible scalability. Bigtable scales in direct proportion to the number of machines in your cluster. A self-managed HBase installation has a design bottleneck that limits the performance after a certain threshold is reached. Bigtable does not have this bottleneck, so you can scale your cluster up to handle more reads and writes.
Simple administration. Bigtable handles upgrades and restarts transparently, and it automatically maintains high data durability. To replicate your data, simply add a second cluster to your instance, and replication starts automatically. No more managing replicas or regions; just design your table schemas, and Bigtable will handle the rest for you.
Cluster resizing without downtime. You can increase the size of a Bigtable cluster for a few hours to handle a large load, then reduce the cluster's size again-all without any downtime. After you change a cluster's size, it typically takes just a few minutes under load for Bigtable to balance performance across all of the nodes in your cluster.