2. The Evolution of Analytics

Question 1

Why is Machine Learning suddenly so popular among business?

Answer 1

Both data storage and data processing capacities have grown tremendously to a point where it is now profitable for businesses to use machine learning

Question 2

Why is a “cold-start” the biggest problem when starting to use Machine Learning?

Answer 2

Most organisations do not have historical data to get started with, they have to start from scratch. It gets easier to use Machine learning when you’ve acquired some data already.

Question 3

What are the 3 types of streaming analytics?

Answer 3

1. Edge analytics - Data colled within the device
2. In-stream analytics - Data collected between the device and the server
3. At-rest analytics - Data collected at rest

Question 4

What are some data quality issues?

Answer 4

1. Noisy Data - Data that contains a large amount of conflicting or misleading information
2. Dirty data - Data that contains missing values, categorical and character features with many levels, and inconsistent and erroneous values.
3. Sparse data - Data that contains very few actual values
4. Inadequate data - Data that is either incomplete or biased