Outsourcing IT needs in the corporate world has become extremely popular because it is cost-efficient and it gives IT resources to companies that may not otherwise be able to afford them. Another positive side effect of IT outsourcing is that it has brought many technology jobs back to the United States.

As convenient and patriotic as IT outsourcing has become, it also have several limitations that have caused many companies to re-think the idea of funding their own internal IT group. It is important for a company to be completely familiar with these limitations before developing any kind of company policy in regards to IT.

The Customer Could Outgrow The Outsource Company

When an IT outsourcing company first takes on a new client, the relationship is beneficial to both sides. But things can start to get inconvenient for the client when the client's business starts to outgrow the capabilities of the IT outsource group.

An IT outsourcing company can become entrenched in the daily routine of its clients, which is great at first. But when the IT company can no longer keep pace with the growth of its clients, then the clients are stuck trying to find a new solution and keep track of its own IT assets at the same time.

The IT Outsourcing Company Lacks The Necessary Technical Expertise

IT outsourcing clients like to believe that their support company knows everything there is to know about computers and the Internet. But every IT support company has its areas of expertise and they have the technical areas where they are not quite as strong. If the client starts to experience needs from the areas where the IT outsourcing company is not so strong, then that can become a significant business issue.

This problem can be amplified if the client is a small business experiencing growth. An IT outsourcing company is not as likely to bring on new personnel for a smaller client, which leaves the client without a solution.

The Client Losses A Measure Of Control Over Its Data

No matter how large or successful an IT outsourcing company may be, there will always be the limitation of client security and the protection of critical customer data. All it takes is one rogue employee of the IT outsourcing company to compromise all of the client's critical data.

Some IT outsourcing companies have safeguards put in place to try and prevent client data compromise, but those safeguards are limited by how much access the IT company has to the client network. In most cases, that access has to be comprehensive for the IT outsourcing company to be able to do its job.

Outsourcing IT responsibilities can take a lot of stress off of a client and allow that client to operate his business by focusing on his core competencies. But there are limitations to IT outsourcing that could make it necessary for a client to do his own IT support and pay the extra costs.

Anonymous reprint from Quora (career advice)

Occasionally we come across a unique profound perspective that makes one stop and really listen. The following advice is one such as this.

1. Small actions compound: Reputation, career trajectory, and how others perceive you in the workplace can come down to a handful of things/moments that seem inconsequential/small at the time but compound. Random Thought: Redwood trees come from small seeds and time. With every action you're planting small seeds and these seeds can grow into something bigger (sometimes unimaginably bigger) over time. Don't let small basic mistakes sabotage your reputation because it only takes a few small snafus for people to lose confidence/trust in your ability to do more important tasks. Trust is a fragile thing and the sooner people can trust you the faster they'll give you more responsibility. Some Examples: Being on time (always) or early (better); spending an extra 10-15 minutes reviewing your work and catching basic mistakes before your boss does; structuring your work so it's easy for others to understand and leverage (good structure/footnotes/formatting); taking on unpleasant schleps/tasks (volunteer for them; don't complain; do it even when there's no apparent benefit to you)  


2. Rising tide lifts all boats: Fact: You don't become CEO of a multi-billion dollar public company in your 30s based purely on ability/talent. Your career is a boat and it is at the mercy of tides. No matter how talented you are it's a lot harder to break out in a sluggish situation/hierarchy/economy than a go-go environment. Even if you're a superstar at Sluggish Co., your upside trajectory (more often than not) is fractional to what an average/below average employee achieves at Rocket Ship Co. There's a reason Eric Schmidt told Sheryl Sandberg to "Get on a Rocket Ship". I had colleagues accelerate their careers/income/title/responsibility simply because business demand was nose bleed high (go go economy) and they were at the right place at the right time to ride the wave. Contrast that to the 2008 bust where earnings/promotions/careers have been clamped down and people are thankful for having jobs let alone moving up. Yes talent still matters but I think people generally overweight individual talent and underweight economics when evaluating/explaining their career successes. Sheryl Sandberg Quote: When companies are growing quickly and they are having a lot of impact, careers take care of themselves. And when companies aren’t growing quickly or their missions don’t matter as much, that’s when stagnation and politics come in. If you’re offered a seat on a rocket ship, don’t ask what seat. Just get on.


3. Seek opportunities where the outcome is success or failure. Nothing in between! You don't become a star doing your job. You become a star making things happen. I was once told early in my career that you learn the most in 1) rapidly growing organizations or 2) failing organizations.  I've been in both kinds of situations and wholeheartedly agree. Repeat. Get on a rocket ship. It'll either blow up or put you in orbit. Either way you'll learn a ton in a short amount of time. Put another way; seek jobs where you can get 5-10 years of work experience in 1-2 years.


4. Career Tracks & Meritocracies don't exist: Your career is not a linear, clearly defined trajectory.  It will be messy and will move more like a step function.


5. You will probably have champions and detractors on day 1: One interesting byproduct of the recruiting & hiring process of most organizations is it can create champions & detractors before you even start the job. Some folks might not like how you were brought into the organization (they might have even protested your hiring) and gun for you at every turn while others will give you the benefit of the doubt (even when you don't deserve one) because they stuck their neck out to hire you. We're all susceptible to these biases and few people truly evaluate/treat folks on a blank slate.


6. You'll only be known for a few things. Make those labels count: People rely on labels as quick filters. Keep this in mind when you pick an industry/company/job role/school because it can serve as an anchor or elevator in the future. It's unfortunate but that's the way it is. You should always be aware of what your "labels" are.


7. Nurture & protect your network and your network will nurture & protect you: Pay it forward and help people. Your network will be one of the biggest drivers of your success.

Here is a list of the organizations that use Python. This list is periodically updated by HSG’s software fans as well as the community at large.
 

Web Development

1.       Yahoo Maps
Yahoo acquired Four11, whose address and mapping lookup services were implemented in Python. Yahoo Maps still uses Python today, as can be seen by examining its URLs.
 

2.       Yahoo Groups
A comprehensive public archive of Internet mailing lists that was originally implemented in pure Python. At one point Scott Hassan, one of the founders of Findmail/eGroups (the company that was later acquired by Yahoo), reported that they had 180,000 lines of Python underlying everything from their 100% dynamic website to all email delivery, pumping out 200 messages/second on a single 400 MHz Pentium.

Python and Ruby, each with roots going back into the 1990s, are two of the most popular interpreted programming languages today. Ruby is most widely known as the language in which the ubiquitous Ruby on Rails web application framework is written, but it also has legions of fans that use it for things that have nothing to do with the web. Python is a big hit in the numerical and scientific computing communities at the present time, rapidly displacing such longtime stalwarts as R when it comes to these applications. It too, however, is also put to a myriad of other uses, and the two languages probably vie for the title when it comes to how flexible their users find them.

A Matter of Personality...

That isn't to say that there aren't some major, immediately noticeable, differences between the two programming tongues. Ruby is famous for its flexibility and eagerness to please; it is seen by many as a cleaned-up continuation of Perl's "Do What I Mean" philosophy, whereby the interpreter does its best to figure out the meaning of evening non-canonical syntactic constructs. In fact, the language's creator, Yukihiro Matsumoto, chose his brainchild's name in homage to that earlier language's gemstone-inspired moniker.

Python, on the other hand, takes a very different tact. In a famous Python Enhancement Proposal called "The Zen of Python," longtime Pythonista Tim Peters declared it to be preferable that there should only be a single obvious way to do anything. Python enthusiasts and programmers, then, generally prize unanimity of style over syntactic flexibility compared to those who choose Ruby, and this shows in the code they create. Even Python's whitespace-sensitive parsing has a feel of lending clarity through syntactical enforcement that is very much at odds with the much fuzzier style of typical Ruby code.

For example, Python's much-admired list comprehension feature serves as the most obvious way to build up certain kinds of lists according to initial conditions:

a = [x**3 for x in range(10,20)]
b = [y for y in a if y % 2 == 0]

first builds up a list of the cubes of all of the numbers between 10 and 19 (yes, 19), assigning the result to 'a'. A second list of those elements in 'a' which are even is then stored in 'b'. One natural way to do this in Ruby is probably:

a = (10..19).map {|x| x ** 3}
b = a.select {|y| y.even?}

but there are a number of obvious alternatives, such as:

a = (10..19).collect do |x|
x ** 3
end

b = a.find_all do |y|
y % 2 == 0
end

It tends to be a little easier to come up with equally viable, but syntactically distinct, solutions in Ruby compared to Python, even for relatively simple tasks like the above. That is not to say that Ruby is a messy language, either; it is merely that it is somewhat freer and more forgiving than Python is, and many consider Python's relative purity in this regard a real advantage when it comes to writing clear, easily understandable code.

And Somewhat One of Performance