mastering the data

Question 1

data nerds

Answer 1

50-90% time on project spent to mater the data
ex: scrubbing, cleaning, cleansing

Question 2

schema

Answer 2

table (rectangle)

Question 3

attributes

Answer 3

nuggets

Question 4

unified modeling language (UML)

Answer 4

relational database

Question 5

relational databases ensure data…

Answer 5

• is complete/ includes all data
• isnt redundant, wont take up too much space
• follow business rules and internal controls
• aid communication and integration of business processes

Question 6

4 types of attributes

Answer 6

• primary keys
• foreign keys
• composite keys
• descriptive attributes

Question 7

primary key

Answer 7

unique identifier

Question 8

foreign key

Answer 8

attributes that point to primary key in another table

Question 9

composite keys

Answer 9

combo of two foreign keys used for line items

Question 10

descriptive attributes

Answer 10

include everything else

Question 11

data dictionaries

Answer 11

legend/ log for full description of each column

Question 12

big 4

Answer 12

currently love alteryx
- extract
- transform
- load
aka cleaning the data

Question 13

requesting data process

Answer 13

1. determine purpose and scope of data request
2. obtain data
3. validate data for completeness and integrity
4. clean the data
5. load the data for data analysis

Question 14

step 1 : determine purpose and scope of data request

Answer 14

• think ahead and plan
  –> what info do I need
  –> where can I get it
  –> how am I going to get it

Question 15

step 2: obtain the data – questions

Answer 15

• do you grab it, or someone else grabs it for you

Question 16

step 2: obtain the data – methods

Answer 16

• obtain yourself

**think about tables, which tables have relations & what attributed are in which table

• data request to IT dept

** if someone else, more complex bc need to explain and bigger orgs have a lot of approval processes

Question 17

step 3: validate data for completeness and integridy

Answer 17

check that data transferred correctly

Question 18

step 4: clean the data

Answer 18

make data consistent
- remove heading or subtotals
- clean leading zeros and nonprint characters
- format neg numbers
- correct inconsistencies
–> dates (6/7/2023 or 7/6/2023 or 2023-07-06)
–> numbers (1 or I, 6 or six)
–> international character encoding (“” or <>)
–> languages and measures (currency signs)
–> human error (23 or 32)

Question 19

step 5: load data for data analysis

Answer 19

import data and make sure functions work properly