Data and Information Flashcards
Data
The initial input of raw facts and figures
Information
Data which has been processed and converted into meaningful output
Internal Information
Information which can be found within the businesses itself, e.g. the profit or loss
External Information
Contextual information that concerns a business, e.g. disposable income of the customers
Quantitative Data
Data that is measurable numerically and is objective, hence more reliable
Qualitative Information
Data that is based on experiences and opinions and is subjective, hence less reliable
Primary Data
Data obtained for a specific purpose through original research conducted by the business itself
Secondary Data
Data obtained by a business from secondary sources
Pros and Cons of Primary and Secondary Data
Primary:
Pros: Collected for a specific purpose
Cons: Reliability depends on staff skill, expensive to produce
Secondary:
Pros: Cost-effective
Cons: Information can be too generic
Adhoc Data
Data required for a specific issue
Continuous Data
Collected and analysed continuously by a business
Good Quality Information
Reliable - from a trusted source
Relevant - directly relates to biz and it’s decisions
Clear - easily read and well presented
Accurate - stats are correct and expressed in the most appropriate way
Targeted - delivered to the right person at the right time
Cost-efficient - info’s usefulness in changing biz process should outweigh the monetary cost of sourcing it
Internal information Sources
Financial info - info from accounting systems e.g. cash books and sales ledgers
Management info - gathered from internal reports e.g. production reports
External Information Sources
Business contacts - info obtained through customers and suppliers
Trade associations - info obtained through trade journals
News media - info obtained through media sources e.g. econ forecasts & social trends
Government - info obtained through gov sources e.g. current GNP or unemployment rates
Big Data
Information which is too large to analyse or interpret using standard reporting facilities
Value of Big Data
Allows info to be drawn from large amounts of different data as opposed to separate sets.
Has potential for almost universal application
Gartner’s 3 Vs of Big Data
Gartner outlined 3 challenges of Big Data in 2001:
Volume - the increasing amount of data being processed makes it harder to extract information
Velocity - the increasing speed of data in and out means it can quickly change.
Variety - the range of types and sources of data makes analysis difficult
Formal Definition of Big Data
High volume, high velocity and/or high variety information that requires new forms of processing which enable advanced decision making, insight discovery and process optimisation
Seven Stages of Big Data
Capture - what data? How to collect it?
Storage - where? IT needs?
Curation - organising the data
Analysis - examine data to make useful info
Visualisation - present data in clear way
Search - allow users to search for info
Data sharing and transfer
Big Data Competitive Advantage
Big data can provide competitive advantage through:
- Production of improved products
- Ensuring stock levels are correct
- Better targeting of marketing campaigns
- Effective pricing strategies
Graphs: Single Bar Charts
Pros:
Simplest
Clear overview of subject being measured
Cons:
Lacks detail
Multiple Bar Charts
Pros:
Separate bar for each product, highlights areas of success and concern
Can be rearranged to show performance of one item over the total period to highlight patterns or consistencies
Cons:
No overall total - to get total sales each month the total for each column would need to be added together
Component/Compound Bar Charts
Pros:
Can see the total value and breakdown per component
Can represent the Y axis as a % and create a % composition graph
Pie Charts
Pros:
Can see the extent to which an element contributes to the total
Provides a clear overview
Cons:
Doesn’t show trends
Info needs further analysis to be useful
