Manual Data Entry
Data Literacy
Building Datasets
- Data has to be collected.
- Surveys are one way.
- Manual/Automated Data Entry is another.
Manual vs Automated Data Entry
- What is Manual Data Entry?
- What is Automated Data Entry?
- What separates the two?
Why are we talking about them together?
- What do they have in common?
- Must design data organization.
- Data entry follows that model.
When do we use it?
- All the time.
- Tracking customer data. (operational/business data) (automated)
- Tracking locations of wildlife. (manual)
- Notes on patient care. (manual/automated)
Problems with Manual Data Entry?
- What did the article indicate?
- Slow.
- Error-prone (up to 4%).
- Expensive.
- Human boredom.
- Inconsistent.
Benefits of Manual Data Entry?
- Handles ambiguity well.
- Handles unstructured/poorly structured data well.
- Can be used to train automated systems.
- Consistency in data entry.
Problems with Automated Data Entry?
- Does not work well will poorly-structured data.
- Prone to false positives and false negatives if not designed well.
Benefits of Automated Data Entry?
- What did the article indicate?
- OCR (optical character recognition) and ICR (Intelligent Character Recognition) are getting better.
- Lowers prices.
- Lowers error rates.
When to use Manual Data Entry?
- When data is unstructured.
- When the information is ambiguous or context specific.
- Gives us better control.
When to use Automated Data Entry?
- When data is well-structured.
- When we can force structure on the data.
- When data follows predictable patterns (for machine learning).
Designing Data Models
- Whatever we choose, we have to organize the data ingestion
- Focus on the smallest unit of data we are interested in.
- Think of these as rows or documents in a database.
Designing Data Models, cont.
- What do we want to track?
- Focus here, then build out.
- We can always aggregate.
- It’s more difficult to break apart.
Example 1: Endangered Birds
- We want to track wild life: endangered birds in a park.
- Manual or Automated?
- What do we need to track?
- We need a list of endangered birds. (know what to look for)
- Nest locations.
- Bird sightings.
Example 1: Endangered Birds, cont
- Nest_Locations
- Bird_ID
- Location (long/lat)
- Date
- Time
- Observer
- Notes
- Bird_Sightings
- Bird_ID
- Location (long/lat)
- Date
- Time
- Observer
- Notes
Example 2: Amazon Customer Data
- We want to track customer purchases and views
- Manual or Automated?
- How do we organize this?
Example 2: Amazon Customer Data, cont.
- Customer_Purchases
- Customer_ID
- Product_ID
- Checkout_ID
- Date
- Timestamp
- Price
- Quantity
- Customer_Views
- Customer_ID
- Product_ID
- Date
- Timestamp
- Price