Data in organization supports business objectives by making decision making Data in healthcare provides precise prescription and research Data in logistics predicts Data in education improves learning exp
DIKW Model Data
- add context to transform into information Information
- connect info to gain knowledge Knowledge
- apply knowledge for better decisions Wisdom
Data-driven decision making: makes the right decisions at the right time
- Asking a good question
- Collecting data, think ahead of analysis
- Prepare data for analysis: clean, arrange
- Analyzing
- Data + experiences of better decision making
Extracting info from data resources
- common aggregation (metrics, benchmarks, KPIs) Data domains
- Data governance: data is trustworthy and not misused
- Data quality: accurate, complete, valid, consistent
- Data Privacy and Security
Data ethics and privacy 5 principles of data ethics:
- Permission: user consents
- Transparancy: how to use, share, collect
- Privacy: PII remains confidentials
- Good intentions: collected for the right reasons
- Outcome *Havard Business School 2021
Data life cycle flows in a predetermined order
Plan and collect > Store and manage > Clean and process > Analysis and Visualise > Share > Archive or destroy
Why
- Ensure data is regualted responsibly
- Identify potential areas for improvements
- Improve effiency and effectiveness of operations
Common mistakes about data
- no clear question or goal
- insufficient or wrong data > bias (doesn't represent all)
- not appropiate statistical method
- no clear communication results
Communicating information
Obtaining insights
- Collect info
- Organize info
- Analyze info
- Determine action plan
- Communicate
- Observe outcome
Best practice: tie insights back to common business objectives for better context Break into smaller ideas
Audience is the most important aspect of communicating: Understand the audience's expected format Tailor the message based on the feedback Keep it simple
- Audience roles
- What do they know
- What do they need to know
- How well do they know me?
Principles of visualization
- Flesh out the trend instead of delving into details
- Keep it simple
Data story sticks
- Visual(core, trend)
- Context(broader picture)
- Narative(make connection, call to action to audience)
Roles
- Subject Matter Expert: bussiness problem completely, develop narative, build context
- Analyst: supporting insight, answer analytical questions
- Visualizer: :|
- Reviewer: evaluate