Uber is a ride-sharing service that was rolled out in 2009 after two of its founders, Travis Kalanick and Garrett Camp c
Posted: Fri Apr 29, 2022 6:45 am
Uber is a ride-sharing service that was rolled out in 2009 after
two of its founders, Travis Kalanick
and Garrett Camp couldn't get a taxi in Paris during a snowstorm.
It originated from the idea, "What
if you could request a ride from your phone?"
Today, Uber boasts an annual revenue of over $11 billion, a market
capitalization rate of $74 billion,
and over 19,000 employees. With 75 million global customers and
three million dedicated drivers in
83 countries, Uber has been a legitimate game-changer in the
ride-sharing services market.
The name Uber is derived from the German word meaning "above all
the rest," a bedrock principle
Kalanick and Camp wanted for their young company. All the riders
need to do is to open their mobile
phone, tap a button, and find an affordable ride in minutes. This
is aligned to the company’s vision
and mission which is to “bring transportation-for everyone,
everywhere.”
What makes Uber so incredibly successful is not its business model,
but how easy it is for people to
work inside of its business model. What Uber has exposed is that
companies can transform a
business if they engage with customers more effectively. But
getting that engagement is tough.
According to Ranney, chief systems architect for Uber, "Each person
connecting to Uber is having a
unique experience with highly personalized data. This level of
personalization at the scale Uber
operates brings problems. Uber's business is not one where the data
can be cached or deployed
through CDNs [content delivery networks]. What complicates issues
is that mobile networks are
simply not as fast as a traditional PC. As an example, the session
time for a typical mobile device is
ten times longer than a PC."
"Another challenge is that Uber cannot afford a system failure.
Ever," said Ranney. "If an Uber
customer cannot get an Uber car, then they will switch to another
app. There is no brand loyalty.
The systems must always work."
Ranney lists three key areas that Uber needs for a fully redundant
system:
• Performance: What types of tests do you run to ensure that your
systems keep
running?
• Data: How can data operate in an environment where a data
connection is
intermittent?
• Future proofing: What technologies does Uber invest in to improve
efficiencies in its
systems?
A common thread through all of Uber's systems is performance,
performance, and performance. Each
technology is chosen because it is the most stable and delivers the
fastest response. In addition to
this, Uber looks to ensure that tools work independently of each
other and are destructible. To this
end, Uber actively attempts to crash its systems, including
networks, databases, and APIs. The system
must work even when it is down. Starting with the mobile apps: Uber
does not use HTML5 or hybrid
solutions in them. All the coding is completed with native code
using the performance and analysis
tools in Xcode and Android Studio.
The level of performance does not stop at the server. The
communication channel, or RPC, is also
modified. Uber's version is called TChannel. It is based on
Twitter's multiplex RPC protocol, Mux. Uber
needed to invent its own RPC communication channel because it
supports more languages than
Twitter. Ranney added, "We are even looking to replace HTTP+JSON, a
typical REST API, with Thrift, as
our tests are showing that it is 20 times faster. We need all the
speed we can get."
Performance for Uber goes to extremes with data. The typical data
structure for a company is a
relational database. The problem that Uber sees with relational
databases is that the whole system
can come down if the database is not available. Uber uses big data
systems as a foundation for its
technologies, with tools such as Riak, Postgres, Redis, and MySQL.
Also, the company is extending
MySQL with its distributed column store to orchestrate the data
processes.
Uber uses drivers' phones as the method of distributing data,
achieving a kind of "super distributed
computing." The result is that stress on replicating data is
eliminated from the data centers. The trick
is achieved by the phone checking in with a server every four
seconds to receive an encrypted digest.
If a server does not respond, the phone moves to a new server. The
whole data environment is
redundant. Also, the more drivers, the more redundancy is added to
the system.
In addition to the core supply-and-demand dispatch systems, Uber
does have a third system: Disco.
Ranney said, "Disco is the dispatch optimization system. Disco's
main function is to match supply with
demand. Disco, however, allows Uber to investigate the future. We
can match predictive supply and
demand, whereas our old system could only match what we knew then."
The advantage Disco
provides Uber is clear: Through data, Uber can help busy drivers
keep efficiently picking up riders. To
do this, Uber needs a global index that requires a massive amount
of data: over 1 million writes per
second. Uber is using Google's S2 Geometry Library to break down
the data and get it out. This library
is designed to split data into smaller geographical sections. The
result is that each section is not
handling only the writes for that geographical location. This in
turns helps the company send drivers
rapid updates on where riders are located and provide more accurate
ETAs for trips. It also gives Uber
the opportunity to expand its business into a specific
geography.
References:
https://techbeacon.com/enterprise-it/ho ... pull-ahead
You Tasks:
After reading the case study above and conducting further research,
you now need to answer the
following research questions below.
1. Critique the alignment between Uber’s information systems
strategy and business strategy.
2. Critically review the role of business intelligence and business
analytics in supporting business
decision making at Uber.
3. Review and evaluate contemporary tools and techniques for
accessing information from
databases to improve business performance.
4. A report of 3000 words summarising your analysis must be
submitted by the due date.
Reasonable assumptions are allowed.
Penalty for Late submission: a deduction of 5% of the total mark
shall be imposed on each of the next
subsequent days.
two of its founders, Travis Kalanick
and Garrett Camp couldn't get a taxi in Paris during a snowstorm.
It originated from the idea, "What
if you could request a ride from your phone?"
Today, Uber boasts an annual revenue of over $11 billion, a market
capitalization rate of $74 billion,
and over 19,000 employees. With 75 million global customers and
three million dedicated drivers in
83 countries, Uber has been a legitimate game-changer in the
ride-sharing services market.
The name Uber is derived from the German word meaning "above all
the rest," a bedrock principle
Kalanick and Camp wanted for their young company. All the riders
need to do is to open their mobile
phone, tap a button, and find an affordable ride in minutes. This
is aligned to the company’s vision
and mission which is to “bring transportation-for everyone,
everywhere.”
What makes Uber so incredibly successful is not its business model,
but how easy it is for people to
work inside of its business model. What Uber has exposed is that
companies can transform a
business if they engage with customers more effectively. But
getting that engagement is tough.
According to Ranney, chief systems architect for Uber, "Each person
connecting to Uber is having a
unique experience with highly personalized data. This level of
personalization at the scale Uber
operates brings problems. Uber's business is not one where the data
can be cached or deployed
through CDNs [content delivery networks]. What complicates issues
is that mobile networks are
simply not as fast as a traditional PC. As an example, the session
time for a typical mobile device is
ten times longer than a PC."
"Another challenge is that Uber cannot afford a system failure.
Ever," said Ranney. "If an Uber
customer cannot get an Uber car, then they will switch to another
app. There is no brand loyalty.
The systems must always work."
Ranney lists three key areas that Uber needs for a fully redundant
system:
• Performance: What types of tests do you run to ensure that your
systems keep
running?
• Data: How can data operate in an environment where a data
connection is
intermittent?
• Future proofing: What technologies does Uber invest in to improve
efficiencies in its
systems?
A common thread through all of Uber's systems is performance,
performance, and performance. Each
technology is chosen because it is the most stable and delivers the
fastest response. In addition to
this, Uber looks to ensure that tools work independently of each
other and are destructible. To this
end, Uber actively attempts to crash its systems, including
networks, databases, and APIs. The system
must work even when it is down. Starting with the mobile apps: Uber
does not use HTML5 or hybrid
solutions in them. All the coding is completed with native code
using the performance and analysis
tools in Xcode and Android Studio.
The level of performance does not stop at the server. The
communication channel, or RPC, is also
modified. Uber's version is called TChannel. It is based on
Twitter's multiplex RPC protocol, Mux. Uber
needed to invent its own RPC communication channel because it
supports more languages than
Twitter. Ranney added, "We are even looking to replace HTTP+JSON, a
typical REST API, with Thrift, as
our tests are showing that it is 20 times faster. We need all the
speed we can get."
Performance for Uber goes to extremes with data. The typical data
structure for a company is a
relational database. The problem that Uber sees with relational
databases is that the whole system
can come down if the database is not available. Uber uses big data
systems as a foundation for its
technologies, with tools such as Riak, Postgres, Redis, and MySQL.
Also, the company is extending
MySQL with its distributed column store to orchestrate the data
processes.
Uber uses drivers' phones as the method of distributing data,
achieving a kind of "super distributed
computing." The result is that stress on replicating data is
eliminated from the data centers. The trick
is achieved by the phone checking in with a server every four
seconds to receive an encrypted digest.
If a server does not respond, the phone moves to a new server. The
whole data environment is
redundant. Also, the more drivers, the more redundancy is added to
the system.
In addition to the core supply-and-demand dispatch systems, Uber
does have a third system: Disco.
Ranney said, "Disco is the dispatch optimization system. Disco's
main function is to match supply with
demand. Disco, however, allows Uber to investigate the future. We
can match predictive supply and
demand, whereas our old system could only match what we knew then."
The advantage Disco
provides Uber is clear: Through data, Uber can help busy drivers
keep efficiently picking up riders. To
do this, Uber needs a global index that requires a massive amount
of data: over 1 million writes per
second. Uber is using Google's S2 Geometry Library to break down
the data and get it out. This library
is designed to split data into smaller geographical sections. The
result is that each section is not
handling only the writes for that geographical location. This in
turns helps the company send drivers
rapid updates on where riders are located and provide more accurate
ETAs for trips. It also gives Uber
the opportunity to expand its business into a specific
geography.
References:
https://techbeacon.com/enterprise-it/ho ... pull-ahead
You Tasks:
After reading the case study above and conducting further research,
you now need to answer the
following research questions below.
1. Critique the alignment between Uber’s information systems
strategy and business strategy.
2. Critically review the role of business intelligence and business
analytics in supporting business
decision making at Uber.
3. Review and evaluate contemporary tools and techniques for
accessing information from
databases to improve business performance.
4. A report of 3000 words summarising your analysis must be
submitted by the due date.
Reasonable assumptions are allowed.
Penalty for Late submission: a deduction of 5% of the total mark
shall be imposed on each of the next
subsequent days.