@Anointe21956866@instablog9ja Good -
Lady aborts her mission - thinking he has seen tweet.
Man proceeds with mission.
Good for man - bad for lady .
Whichever way - Comrade has done well .
Finally! I’m happy to share that I have completed my Udacity Data analyst Nanodegree
I got my certificate last week but I was sick and I had a small accident but I’m fine now 😁
Allow me to share a bit of my journey and the strategy I used to finish well
A thread🧵
This week @DataCamp is giving away all it's courses for free.
Python. SQL. Tableau. Power BI.
And all things Data.
For FREE.
ALL WEEK.
https://t.co/S0Ih4oJKl2
@BooooooZahhhhhh@fantasyrebel @viralhoodfights He said facts ! I am black , I have always wondered why black women are embarrassed by their natural hair . The level of low self esteem .. fake hair,Fake lashes , fake everything Damn
@BooooooZahhhhhh @viralhoodfights They are the only ones who fight half naked with fake hair…they are the only ones who are embarrassed when their real hair gets exposed…no other group of women have such low self esteem where they’d be ashamed of showing their natural hair
Junior data scientists are told the problems they need to solve 👶
Senior data scientists find the problems that need to be solved 😎
Here is how they do it ↓↓↓
@ZubyMusic Don't silence yourself. Sometimes you need to speak up for yourself if you can. If you stay quiet out of fear of causing conflict between you and another person. . .you're only hurting yourself and helping nothing.
@Aakriti_Sarma 1. Sit down with the client/resource person/team and discuss the objectives for the visualization/presentation.
2. Fetch/source the data.
3. Clean the data (if needed)
4. Model the data to match the needed fields/dimensions
Steps 5-8: 👇🏽
@Aakriti_Sarma 5. Hand-draw the initial look of the dashboard on paper (old fashioned like that 😁)
6. Create the initial build of the dashboard
7. Present to the client/resource team for initial comments/dry-run
8. Make tweaks/edits (if needed)
9. Publish DB & set for auto refresh (if needed)