Question

1. Define big data and data mining.
2. What purpose does collecting huge amounts of data serve?
3. Consider Twitter. Do you believe big data is accurate and reliable? Why or why not?
4. What type(s) of sampling methods could be used with big data?
5. What sampling errors could occur and how could they be avoided?
6. Has collecting big data been helpful for businesses? Why or why not?
7. What do you see happening in the future with big data?

Answer 1

ANSWER::

Explanation:

1. Big data is simply defined as a large amount of data whereas data mining is simply the extraction of key information from either a small or a large amount of data
2. The major purpose of collecting huge amounts of data is usually to identify different patterns of data that may be hidden.
3. I do not believe that big data in twitter is reliable and accurate. This is because, the big data(tweets) cannot be relied to be an honest representation of the user.
4. There are quite a number of sampling methods that could be used with big data. For example; inverse sampling and data integration.
5. Examples of sampling errors are;

• Population specification errors which basically occurs when researchers don't understand who they should survey.
• Sample frame errors. This are errors that occur as a result of using the wrong population of people to collect data.

There are various ways of avoiding these errors. Such as; ensuring careful sample designs and using larger samples.

6 . Collecting big data is very helpful in the business world because it enables the marketer to understand his customers better and also understanding the market conditions of his products and services.

7 . Big data is mostly associated with issues of privacy but in the future, this issue is going to be resolved.

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