Transforming data into information

Turning data into information is just a beginning

Data - This can be described as the raw data that would typically support or part of an operational processes.

Information - Transformed information is consumable for reporting and analytical needs. - "What does it mean?"

Knowledge - Taking the Information we have prepared in the previous step and enriching it with relationships and correlations that start to "tell the story" of what the data contains. - "What do we already know and why?"

Intelligence - The holy grail, we have leveraged all the previous stages to put all this data to address the problems/issues or challenge - "What do we do?"

Stages of data analysis

Editing

Coding

Data file

Analysis approach

Descriptive analysis

Univariate analysis

Bivariate analysis

Multivariate analysis

Editing

The process of checking the completeness, consistency, and legibility of data and making the data ready for coding and transfer to storage.

Field Editing

• Field supervisors often are responsible for conducting preliminary field editing on the same day as the interview.

• Field editing is used to– Identify technical omissions such as a blank p

age on an interview form– Check legibility of handwriting for open-ended

responses– Clarify responses that are logically or concept

ually inconsistent.

in-house editing

• A rigorous editing job performed by a centralized office staff

Editing for Completenessitem nonresponsePlug valueImpute

Editing Questions Answered Out of Order

Facilitating the Coding Process

• Eding and Tabulating “DON’T KNOW” answer• Pitfalls of editing• Pretesting edit

Coding Qualitative Responses

• Unstructured qualitative responses (Long Interviews)

• Structured qualitative reponse– dummy coding Numeric “1” or “0” coding wher

e each number represents an alternate response such as “female” or “male.”

– Data file terminology The way a data set is stored electronically in spreadsheet-like form in which the rows represent sampling units and the columns represent variables.

Summary

• Know when a response is really an error and should be edited

• Appreciate coding of pure qualitative research• Understand the way data are represented in the

data file• Understand the coding structure of responses

including a dummy variable approach• Appreciate the ways that technological advances

have simplified