Small and Big Data

Question 1

What is mathematical thinking?

Answer 1

A skill that can be used to solve problems and see new solutions

Question 2

eh

What does using a mathematical approach mean?

Answer 2

• Looking at a problem and logically breaking it down step-by-step so you can see the relationship of patterns in your data, and use that to analyze your problem
• Looking at different aspects of a problem to choose the best logical approach and figure out the best tools for analysis.

Question 3

What are some characteristics of small data?

Answer 3

• Typically made up of datasets concerned with specific metrics over a short, well defined period of time.
• Usually organized and analyzed in spreadsheets
• Likely used by small and mid-sized businesses
• Simple to collect, store, manage, sort and visually represent
• Usually already a manageable size for analysis
• Useful when making day-to-day decisions
• Has a small impact on large frameworks

Question 4

What are some characteristics of big data?

Answer 4

• Larger, less specific datasets covering a longer period of time.
• Typically kept in a database and queried
• Likely to be used by large organizations
• Takes a lot of effort to collect, store, manage, sort and visually represent

Question 5

What are some challenges with big data?

Answer 5

• A lot of organizations deal with data overload and way too much unimportant or irrelevant information.
• Important data can be hidden deep down with all of the non-important data, which makes it harder to find and use. This can lead to slower and more inefficient decision-making time frames.
• The data you need isn’t always easily accessible.
• Current technology tools and solutions still struggle to provide measurable and reportable data. This can lead to unfair algorithmic bias.
• There are gaps in many big data business solutions.

Question 6

What are benefits of big data?

Answer 6

• When large amounts of data can be stored and analyzed, it can help companies identify more efficient ways of doing business and save a lot of time and money.
• Big data helps organizations spot the trends of customer buying patterns and satisfaction levels, which can help them create new products and solutions that will make customers happy.
• By analyzing big data, businesses get a much better understanding of current market conditions, which can help them stay ahead of the competition.
• As in our earlier social media example, big data helps companies keep track of their online presence—especially feedback, both good and bad, from customers. This gives them the information they need to improve and protect their brand.

Question 7

What is one way to decide which tool to use for analysis?

Answer 7

• The size of your data set
• Small amounts of data may be better suited to a spreadsheet for analysis

Question 8

You are the three V’s of big data?

Answer 8

• Volume
• Variety
• Velocity

Question 9

What is the possible fourth V that some data analysts consider?

Answer 9

Veracity

Question 10

What is volume in the three V’s of big data?

Answer 10

The amount of data

Question 11

What is Variety in the three V’s of big data?

Answer 11

The different kinds of data

Question 12

What is Velocity in the three V’s of big data?

Answer 12

How fast the data can be processed

Question 13

What is definition of Veracity, the fourth V some analysts use in big data?

Answer 13

The quality and reliability of the data

Question 14

What is the lifecycle of data?

Answer 14

1. Plan
2. Capture
3. Manage
4. Analyze
5. Archive
6. Destroy

Question 15

What is data cleaning?

Answer 15

• The process of fixing or removing incorrect, corrupted, incorrectly formatted, duplicate, or incomplete data within a dataset.
• When you find and fix the errors - while tracking the changes you made - you can avoid a data disaster.