Digital: Data and analysis Flashcards
What is data?
1: factual information (such as measurements or statistics) used as a basis for reasoning, discussion, or calculation;
2 :information in digital form that can be transmitted or processed; and
3 :information output by a sensing device or organ that includes both useful and irrelevant orredundantinformation and must be processed to be meaningful
Data vs information
Data: raw, unprocessed facts and figures
Information: data that has been processed in a way that makes it meaningful for planning and decision making
’information in digital form
Digital Form:
1 and 0 = 1 bit (binary system)
10101010 = 8 bits = 1 byte
data Size
If in weight 1000g = 1kg then 1000 Bytes should be 1KB (Kbyte)
A kilobyte is approximately 1,000 bytes (in fact 1,024 bytes)
Financial data
Standard metrics checked and best understood by the organization
Enterprise data
Financial data plus broad operational and transactional data that bolsters analysis and forecasting
Big data
Enterprise data Communicating the above insights to users and contributing to an objective, responsible perspective to influence their decision making
What is Big Data?
Big Data is an emerging technology that has implications across all business departments. It involves the collection and analysis of large amounts of data to find trends, understand customer needs and help organisations to focus resources more effectively.
Big Data has a role to play in information management
Collecting data
Formal data collection
This happens when an organisation needs specific data to fulfil a particular purpose.
Informal data collection
Happens continuously, e.g. when employees learn about what is going on around them
via newspapers, websites, etc.
Sources of Data
Internal Sources
Accounting record
Human resources
Production data
Sales and marketing data
Timesheet
External Sources
Customers – product requirements & price elasticity
Libraries & information services
Newspapers, journals & the internet
Government agencies i.e. Stats SA or SARS
Structured data
Clearly defined data types within a structure.
Normally this structure is a type of database and / or other file where the data is stored in rows and columns.
Recorded in predefined fields and formatted appropriately.
Allows for easy manipulation and analysis
Quantitative and qualitative information
Qualitative Information
Can be given a value, e.g. $100m
Financial statements: Balance sheets, income statements, and cash flow statements that provide numerical data on a company’s financial performance.
Stock prices: The price of a company’s stock can be measured and tracked over time.
Interest rates: The rate at which money can be borrowed or invested can be measured and analysed to determine financial strategy.
Quantitative Information
Cannot be given a value, colour, subjective rating
Market sentiment: The overall mood of investors and traders can influence stock prices and financial trends.
Brand reputation: A company’s brand reputation can affect its long-term financial success and value.
Customer satisfaction: The opinions and experiences of customers can influence a company’s financial performance
Qualities of information
Accurate
Complete
Cost-effective
Understandable
Relevant
Accessible
Timely Easy-to-use
Data modelling
Analysis of an organisation’s data needs to support its business processes
Data manipulation
Reorganisation or transformation of data to make it easier to read or more meaningful
Data analysis
Overall process of collecting, cleansing, manipulating and modelling data to support decision making.
