"On the topic of personalisation the main complexity comes from stitching the data together so that you can create a curated and hopefully personal experience for the consumers (e.g. product offer that match user's interest).
Since the existing technology we use, especially on the app, do not support some of of the BE foundations needed to personalize omni-channel the main complexity is in integrating with the BE services especially creating connected data pipelines. My main contribution is in"
Delyan P. - "On the topic of personalisation the main complexity comes from stitching the data together so that you can create a curated and hopefully personal experience for the consumers (e.g. product offer that match user's interest).
Since the existing technology we use, especially on the app, do not support some of of the BE foundations needed to personalize omni-channel the main complexity is in integrating with the BE services especially creating connected data pipelines. My main contribution is in"See full answer
"i asked if she meant operations business analytics metrics.. she clarified that she meant operational/stability metrics.. i explained that i used dynatrace to monitor the product and she said i want to know about SLAs etc. she was looking for the words SLA SLO and SLI.. i then explained SLA 99.99% various SLO's contributed to it like system uptime, continous testing of business functions, and incident mgmt metrics."
Sayee M. - "i asked if she meant operations business analytics metrics.. she clarified that she meant operational/stability metrics.. i explained that i used dynatrace to monitor the product and she said i want to know about SLAs etc. she was looking for the words SLA SLO and SLI.. i then explained SLA 99.99% various SLO's contributed to it like system uptime, continous testing of business functions, and incident mgmt metrics."See full answer
"The solution produces the same result as the 'prescribed solution' yet it does not get accepted In the test results section
transcript['year'] = transcript['year'].astype(str)
df = pd.pivottable(data = transcript, index = 'studentid', columns = 'year', values = 'yearlygpa', aggfunc = 'mean').resetindex()
df = df[(df['2021'] < df['2022']) & (df['2022'] < df['2023'])]
df['average_gpa'] = df[['2021', '2022', '2023']].mean(axis=1).round(2)
return df
"
Prachi G. - "The solution produces the same result as the 'prescribed solution' yet it does not get accepted In the test results section
transcript['year'] = transcript['year'].astype(str)
df = pd.pivottable(data = transcript, index = 'studentid', columns = 'year', values = 'yearlygpa', aggfunc = 'mean').resetindex()
df = df[(df['2021'] < df['2022']) & (df['2022'] < df['2023'])]
df['average_gpa'] = df[['2021', '2022', '2023']].mean(axis=1).round(2)
return df
"See full answer
"if decreasing arr, start from end and keep checking if next element increases by 1 or not. wherever not, put that value there."
Rishabh R. - "if decreasing arr, start from end and keep checking if next element increases by 1 or not. wherever not, put that value there."See full answer
"Facebook groups operate to inculcate community interaction. I would deep dive into the current user behavior to understand a lot more
User journey
User age groups that show most activity
Usage of features
Dominant topics
Any other data point that will provide insight to usage statics
Based on above findings, I would devise a feature that would target increasing retention/time spent on the groups by incentivizing high performing user and/or user groups.
Some examples of features"
Priyanka V. - "Facebook groups operate to inculcate community interaction. I would deep dive into the current user behavior to understand a lot more
User journey
User age groups that show most activity
Usage of features
Dominant topics
Any other data point that will provide insight to usage statics
Based on above findings, I would devise a feature that would target increasing retention/time spent on the groups by incentivizing high performing user and/or user groups.
Some examples of features"See full answer
"Clarifications:
Do we consider window for any building or only residences? I will ignore windows in cars for complexity reasons.
Pardon my ignorance for not knowing the size and population of Tehran, Would you mind sharing some inputs or is it okay if pick some Randoms?
Analysis:
Tehran is ~300 sq. miles in terms of land area with an overall population of 9 MM with an average 3.5 members per household.
_I will be moving with windows for residences only and then gut check my response"
RockyBalboa - "Clarifications:
Do we consider window for any building or only residences? I will ignore windows in cars for complexity reasons.
Pardon my ignorance for not knowing the size and population of Tehran, Would you mind sharing some inputs or is it okay if pick some Randoms?
Analysis:
Tehran is ~300 sq. miles in terms of land area with an overall population of 9 MM with an average 3.5 members per household.
_I will be moving with windows for residences only and then gut check my response"See full answer
"LinkedIn is a Corporate/Professional Networking platform. We will analyze the following factors before the launch:
How many people of the demography are on LinkedIn
I will make sure Learning platform content is approved, verified and required for interviewing for a specific role in a corporate
Create a Learning Community where people who opt for the LinkedIn learning platform share their experience of the completed course and how it helped them get an interview opportunity with the comp"
Akshat A. - "LinkedIn is a Corporate/Professional Networking platform. We will analyze the following factors before the launch:
How many people of the demography are on LinkedIn
I will make sure Learning platform content is approved, verified and required for interviewing for a specific role in a corporate
Create a Learning Community where people who opt for the LinkedIn learning platform share their experience of the completed course and how it helped them get an interview opportunity with the comp"See full answer
"Clarifications
Shared laundry means there are a number of washers and dryers in a room, and anyone can pay to use those for one cycle
Assuming minimal hardware changes to washers and dryers
Goal: Improve customer satisfaction with the shared laundry experience
Metric: Customer satisfaction score (TBD)
Users:
Customers
Low volume (e.g. singles, young professionals etc.) (L, XL)
Medium volume (e.g. families with children or elderly etc.) (XL, S)
Large volume (e.g. re"
AspiringNoogler - "Clarifications
Shared laundry means there are a number of washers and dryers in a room, and anyone can pay to use those for one cycle
Assuming minimal hardware changes to washers and dryers
Goal: Improve customer satisfaction with the shared laundry experience
Metric: Customer satisfaction score (TBD)
Users:
Customers
Low volume (e.g. singles, young professionals etc.) (L, XL)
Medium volume (e.g. families with children or elderly etc.) (XL, S)
Large volume (e.g. re"See full answer
"Let's start by describing a time machine, which is a device that allows somebody to move backwards or forwards in time.
The movement could be physical movement, wherein the user gets physically transported to a different timeline, or it could be getting a glimpse into a different timeline, like wearing a VR headset and getting to experience a different timeline without physically being there. For the purpose of this exercise, I will assume, this time machine allows a person to physically trans"
Akshay R. - "Let's start by describing a time machine, which is a device that allows somebody to move backwards or forwards in time.
The movement could be physical movement, wherein the user gets physically transported to a different timeline, or it could be getting a glimpse into a different timeline, like wearing a VR headset and getting to experience a different timeline without physically being there. For the purpose of this exercise, I will assume, this time machine allows a person to physically trans"See full answer