# data[].attributes.body
1. Data Attributes

2. Data Quality Assessment

3. Data Cleaning

# data[].attributes.headline
Presenting data visually? Charts / Histogram 

# data[].attributes.subject
Presenting data visually? Charts / Histogram 

# data[].attributes.body
Errors in data can be due to faulty data collection instruments, data entry problems, data transmission problems, tech limitations, inconsistency in naming

# data[].attributes.headline
Clean data to ensure more accurate analysis

# data[].attributes.subject
Clean data to ensure more accurate analysis

# data[].attributes.headline
Data anomaly might be a data defect - April 2020 bubble tea price shot skyhigh

# data[].attributes.subject
Data anomaly might be a data defect - April 2020 bubble tea price shot skyhigh

# data[].attributes.body
recode/standardize inconsistent data