Data and Information basics

Data = The record of an event or fact. 

Information = Data that has been processed for a purpose

Information is data that has been processed or re-structured in some way. It can also be seen as:

• A thing that exists somewhere
• A process that leads to a change in someone's knowledge

Data = The building blocks for information

• Facts/observations/measurements
• Example
  • Data: temperature is 25 degrees, the town is Hounslow
  • Information: The temperature is 25 degrees in Hounslow

Data needs to be structured and processed well for information to be generated

Metadata provides an interface between user/system and data tables, fields and records:

• Metadata - Data based on data. (Data description)
• Lets user work with a dataset.
• Describes properties, such as name, size and scope.

Data is often stored in a table that consists of rows and columns.

Rows represent distinct records and their common attributes, whereas columns represent distinct fields associated with records.

The point where a column and row cross is known as a cell.

Cells hold the value of that field for that record.

Table of numbers doesn't mean anything unless uses metadata to provide context.

Such examples include:

• Table names
• Variable names

Readability can also be improves if categories are labelled.

Data processing = Collection and manipulation of items of data to produce meaningful information.

It's part of a broader process of data analysis:

• Where objective include exploration, confirmation and decision making.
• Data processing involves organising data into a way that supports further operations necessary to achieve the overall goals of data anlysis.
• Other steps include checking, cleaning, visualising and modelling data.
• Classification - Arranging cases by group
• Summarising - compressing sets of cases into sums, counts or averages.
• Rearranging data - Putting data into an order that suits the user, e.g. by ascending age.

Calculations can also be made on the data along with selection.

Information lets us make decent decisions by reducing or uncertainty about the world.

Information needs can be defined by a question, such as:

• What profit did the company make in the last quarter?
• Should we make an offer for house A or B?

This shows that it is vital for information to have validity and reliability to it.

Generating information always has a cost for data collection, processing and storage.

The value of the information is better decision making and it can also be quantifiable:

• Increased revenue
• Costs and response times going down
• Relative to the information costs.

Information is not always quantifiable as it's not always possible to separate the effect of information from other factors and can lead to improved staff motivation, as well as be good for decision making. The impact may not be immediate, but information may maintain a general understanding of an area.

There are three types of decision making that have different levels of decision making:

• Strategic planning - Long term
• Tactical planning and control - Mid term
• Operational planning and control - Short term

Different decision making scenarios can range betwen structured and unstructured. For example:

• Unstructured strategic planning can include company reorganisation.
• Structured management control can include allocating budgets.
• Semi-structured operation contol can include short-term production rescheduling.

Research = Process of steps used to collect and analyse information to increase understand of a topic or issue.

Research has 4 main steps:

• Asking questions
• Collecting data
• Data analysis
• Answer presentation

Research is extremely important, both academically an commercially.

Some goals of research can include:

• Exploratory - defining the nature of a problem
• Constructive - finding a solution to a problem
• Empirical - testing hypotheses
• When one goal is achieved, it often leads to another.

There are different types of research that people partake in:

• Primary vs secondary research - does the knowledge already exist or do we need to find out ourselves?
• Laboratory vs field studies - are we able to collect reliable data by studying the phenomenon in the wild or do we need tighter control over the variable needed?
• Cross sectional vs longitudinal - can the phenomenon be measured in a short intervention or is it needed to measure it over an extended period?

There are a number of specific data collection methods:

• Observation
• Task performance
• Questionnaires
• Interviews
• Diary studies

Information generated by analysing the data and interpreting outputs.

• Data must be checked, cleaned and coded
• Interpreted using tables, charts and statistics

• Data are basic facts or observations
• Information is created by processing and restructuring data
• Information aids good decision making, which reduces uncertainty
• Information requirements depend upon the level and type of decision being made
• Information has both quantifiable and unquantifiable value
• Data that has been collected is typically represented as a table comprising of rows (records) and fields (columns)
• Metadata describes the properties of the data
• Classification, aggregation, sorting, summarisation, calculations and selection are basic processes by which data is used to “inform”
• We carry out research to establish the facts relating to problems/questions that we face
• There are three main kinds of research – exploratory, constructive and empirical
• The methods used to collect and analyse data vary according to the problem and type of research