Data has always been important to business. While it wasn't long ago that businesses kept minimal information on people who bought their products, nowadays companies keep vast amounts of data. In the late 20th century, marketers began to take demographics seriously. It was hard to keep track of so much information without the help of computers.

Only large companies in the '60s and '70s could afford the research necessary to deliver real marketing insight. The marketers of yesteryear relied upon focus groups and expensive experiments to gauge consumer behavior in a controlled environment. Today even the smallest of companies can have access to a rich array of real-world data about their consumers' behavior and their consumers. The amount of data that is stored today dwarfs the data of only a few years ago by several orders of magnitude.

So what kind of information are businesses storing for marketing purposes? Some examples include:

- Demographic information — age, gender, ethnicity, education, occupation and various other individual characteristics.

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

Cloud computing is the recent rage in the IT industry. According to the report by Forbes, the estimated global market for cloud computing is expected to reach $35.6 billion in 2015, from the $12.1 billion market of 2010.

How it began

The idea of cloud computing was inspired by the concept of “utility computing” which introduced the idea of computing using the virtual servers. These virtual servers do not actually exist anywhere physically and can be moved anywhere without causing any disturbance to the end users. Thus it minimizes the cost involved on the devices to a great extent and provides innumerable benefits to the companies that adopt this system.

Cloud Computing Types

The iconic software company that is based in King County Washington has been getting almost universally slammed from it's recent Los Angeles press announcement about its entry into the hardware business with the convertible laptop/tablet known as Surface.

Certainly I can see the point that it is now competing with its hardware vendors/partners. Intel has done a good job in the arena creating 'reference designs' without competing with its partners.

There is another viewpoint which seems to be ignored. The cold facts are Microsoft is a public company. This puts Microsoft in a legal position of doing the most it can to return value to its shareholders. Failure to do so means somebody is going to jail.

Microsoft has a vision, which at the end of the day is, a certain way to get enough people to see enough value to hand over their money, to fulfill their fiduciary duty.