Big data is now in an incredibly important part of how many major businesses function. Data analysis, or the finding of facts from large volumes of data, helps businesses make many of their important decisions. Companies that conduct business on a national or international scale rely on big data in order to plot the general direction of their business. The concept of big data can be very confusing due to the sheer scale of information involved.  By following a few simple guidelines, even the layman can understand big data and its impacts on everyday life.

What Exactly is Big Data?

Just about everyone can understand the concept of data. Data is information, and information is everywhere in the modern world. Anytime you use any piece of technology you are making use of data. Anytime you read a book, skim the newspaper or listen to music you are also making use of data. Your brain interprets and organizes data constantly from your senses and your thoughts.

Big data, much like its name infers, simply describes this same data on a large sale. The internet allowed the streaming, sharing and collecting of data on a scale never before imaginable and storage technology has allowed ever increasing hoards of data to be accumulated. In order for something to be considered “big data” it must be at least 10 terabytes or more of information. To put that in perspective, consider that 10 terabytes represents the entire printed collection of material in the Library of Congress. What’s even more remarkable is that many businesses work with far more than the minimum 10 terabytes of data. UPS stores over 16 petabytes of data about its packages and customers. That’s 16,000 terabytes or the equivalent to 1,600 printed libraries of congress. The sheer amount of that data is nearly impossible for a human to comprehend, and analysis of this data is only possible with computers.

How do Big Data Companies Emerge?

All of this information comes from everywhere on the internet. The majority of the useful data includes customer information, search engine logs, and entries on social media networks to name a few. This data is constantly generated by the internet at insane rates. Specified computers and software programs are created and operated by big data companies that collect and sort this information. These programs and hardware are so sophisticated and so specialized that entire companies can be dedicated to analyzing this data and then selling it to other companies. The raw data is distilled down into manageable reports that company executives can make use of when handling business decisions.

The Top Five:

These are the five biggest companies, according to Forbes, in the business of selling either raw data reports or analytics programs that help companies to compile their own reports.

1. Splunk
Splunk is currently valued at $186 million.  It is essentially a program service that allows companies to turn their own raw data collections into usable information.

2. Opera Solutions
Opera Solutions is valued at $118 million. It serves as a data science service that helps other companies to manage the raw data that pertains to them. They can offer either direct consultation or cloud-based service.

3. Mu Sigma
Mu Sigma is valued at $114 million.  It is a slightly smaller version of Opera Solutions, offering essentially the same types of services.

4. Palantir
Palantir is valued at $78 million.  It offers data analysis software to companies so they can manage their own raw data analysis.

5. Cloudera
Cloudera is valued at $61 million.  It offers services, software and training specifically related to the Apahce Hadoop-based programs.

The software and services provided by these companies impact nearly all major businesses, industries and products. They impact what business offer, where they offer them and how they advertise them to consumers. Every advertisement, new store opening or creation of a new product is at least somewhat related to big data analysis. It is the directional force of modern business.

Sources:
http://www.sas.com/en_us/insights/big-data/what-is-big-data.html

http://www.forbes.com/sites/gilpress/2013/02/22/top-ten-big-data-pure-plays/

http://www.whatsabyte.com/

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Is the U.S. the Leading Software Development Country?

How to Keep On Top Of the Latest Trends in Information Technology

IT Outsourcing came to foray as a means for corporations to focus on critical business operations while having a specialized IT company take over the responsibility of managing the IT infrastructure and application development. For corporations especially in the developed countries, IT outsourcing provided two fold advantages, one was access to a highly talented pool of engineers and that too at a lower cost since countries like India were quickly growing their stature as an IT outsourcing hub.

IT Outsourcing is now as mainstream as ever and almost every leading organization outsources some or all parts of its IT infrastructure to a specialized company. It makes pure business sense and with tightening budget controls, IT outsourcing has become one of the strategic cost reduction driver for most organizations. Moreover, IT outsourcing is no more restricted to companies in USA & Europe outsourcing their IT projects to countries like India. Domestic companies within India itself actively use IT outsourcing including the Indian government like the India Post project given to TCS.

Is it then a no brainer that IT Outsourcing is critical to your business? Well, if it is cheaper and does not seem to have any inherent disadvantages why not!! Not really, IT Outsourcing despite proven benefits has its limitations and you should be cognizant be of the same before considering outsourcing your IT operations.

·         Limitations in estimating the actual cost of IT outsourcing:Let’s tackle the biggest driver of IT Outsourcing-Cost Savings. For anyone to estimate the cost savings from IT Outsourcing one needs to be able to predict the cost of outsourcing which then helps understand the cost savings from the same. Yes, at a higher level it is a matter of a simple $ per man-hour costs and IT outsourcing will appear to be cheaper in almost all cases. However, “hidden costs” are commonplace with IT outsourcing and it can be immensely difficult to accurately predict these hidden costs. For example, you need to be able to identify the costs of transitioning your in-house IT to an outsourcer, management overhead needed to manage the outsourcing relationship etc. In addition, IT outsourcing contracts are fixed at the start of the contract and as a result any additional requirement/change tends to be charged additionally. It is no surprise that IT requirements can change frequently and if your outsourcing contract doesn’t account for flexibility, you might be limited in the actual cost savings you might make. There is no surprise that there have been so many instances of IT outsourcing projects overshooting their budgets by a huge margin such as the one government shared services project going 500 million pounds over budget

A project manager acts as the primary link between business and technical teams. A project manager is responsible for maintaining the project schedule, developing project estimates, working with external teams and tracking project issues. The project manager belongs to either the technical team or the project management office (PMO). The project manager works with business teams, technical teams, business counterparts, testing resources, vendors and infrastructure teams.

A project manager is often challenged with diagonally opposite views from the business side and technical side. A project manager’s success depends on balancing the needs and emotions of both sides.

Understanding the Requirements
A project manager must familiarize with the project’s requirements as defined by the business or product managers. This will help you understand the business vision behind the project. You will need this knowledge while negotiating with the technical teams.

Understanding the Technical Landscape
A project manager must also understand the technical systems, resource skills and infrastructure capabilities available for the project. Business teams come up with expectations that are sometimes beyond the capabilities of the technology team. It is the responsibility of the project manager to understand the technical capabilities available to the project.

Walkthrough of Business Requirements
This is a critical step in the project delivery process. The project manager must invite members from the business team, technical team, testing team, infrastructure team and vendors. The project manager must encourage the various stakeholders to ask questions about the requirements. Any prototypes available must be demonstrated in this meeting. The project manager must find answers to all questions resulting from the requirements walkthrough. The project manager must get the final version of the requirements approved by all stakeholders.

Managing Conflicts in Timelines and Budgets
All project managers will face the conflicts arising from shortened timelines and limited budgets. Business teams typically demand many features that are nearly impossible to deliver within short timeframes. The project manager must work with business and technical teams to prioritize the requirements. If the project is executed in a product development organization, then the project manager could utilize agile methodologies to deliver projects incrementally. In this case, the project manager may be required to act as a scrum master to facilitate scrum meetings between various stakeholders.

The Art of Saying “No”
As a project manager, you may be forced to say “no” to demands from both business and technology teams. However, it is important to create a win-win situation for all parties when you are faced with conflicting demands. You can work with the stakeholders individually before bringing all parties together. Most stakeholders prefer to work together. The success of a project manager depends on how effectively he or she can bring out the best in everyone, driving everyone towards a common goal.

Finally, the job of a project manager is not to satisfy the demands from all corners. The project manager must identify the essential deliverables that will meet the business needs, with a solid understanding of what is possible within the limits of technology.

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Is Agism an Issue in IT?

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