what is good dataset?

 

 

First things first, we need 

to learn how to identify good data set!

.I can make it easy for you 

acronyms:

                                                            R-O-C-C-C                                                                                             

 

R for reliable. 

    Like a good friend, good data sources are reliable.

With this data you can 

trust that you're getting accurate, 

complete and unbiased information 

that's been vetted and proven fit for use.

O is for original. 

    There's a good chance you'll discover data 

through a second or third party source. 

To make sure you're dealing with good data, 

be sure to validate it with the original source.

C is for comprehensive. 

    The best data sources contain 

all critical information needed to 

answer the question or find the solution. 

Think about it like this. 

You wouldn't want to work for a company just because you 

found one great online review about it. 

You'd research every aspect of 

the organization to make sure it was the right fit. 

It's important to do the same for your data analysis.

C is for current. 

    The usefulness of data decreases as time passes. 

If you wanted to invite 

all current clients to a business event, 

you wouldn't use a 10-year-old client list. 

The same goes for data. 

The best data sources are current 

and relevant to the task at hand.

C is for cited. 

    If you've ever told a friend where you heard 

that a new movie sequel was in the works, 

you've cited a source. 

Citing makes the information 

you're providing more credible. 

When you're choosing a data Sources, 

think about three Question. 

Who created the data set?

Is it part of a credible organization? 

When was the data last refreshed? 

If you have original data from 

a reliable organization and it's

comprehensive, 

current, and cited, it ROCCCs! 

There's lots of places that are 

known for having good data. 

Your best bet is to go with the vetted public data sets, 

academic papers, financial data, 

and governmental agency data.

 

Now that you know how to spot the good data, which ROCCCs, 

you're ready to learn about the mountain of 

bad data and how to avoid it. Let's get moving.