Consumerization is described as the trend for IT to first emerge in the Consumer space and subsequently makes its way into the enterprise world. But what exactly in the consumer world, that is making the users, demand the similar things from the enterprise IT. To understand the underlying need, we need to first examine the basic requirements of the user.

Kathy Sierra, co-creator of the Head First series of books and founder of javaranch.com, describes the hierarchy of needs from the user(s) perspective. The needs are stacked in the order of increasing engagement from the user. Starting with the basic needs of a defined functionality and its correctness, moving on to the learnability, efficiency & usability and finally culminating in intuitiveness and enchantment. Merely provision of correctly working functionality is not guarantee of the success of the application(s). The idea is to hook the user; the application needs to do something extra.

Using the hierarchy of needs as the background, we will see how the applications in the consumer and enterprise world stack up.

Bigdata has caught the fancy of each and everyone. Consumer and enterprise world is looking to adopt the Bigdata. Analysts are talking about it, proclaiming it to the next big thing!

This is my take on how the Bigdata market space will evolve in 2012 and years to come.

• Data Analytics Service – We will start seeing SaaS vendors that will start offering data analytics as a service (e.g. 1010data). These vendors will be able to pull in your unstructured data and provide you standardized reports and data services. This is very similar to the Web analytics (like Omniture) but access lot more data to provide patterns. 70-80% of the data analysis pattern will be similar across industries. These vendors will be able to provide these reports as off the shelf capabilities. For the other 20%, the web interface will allow the user to create patterns to analyze the data

Any application you pick up, there are some issues – big or small. There will be copy-paste code, mistakes, algorithms which could have better thought through. But what distinguishes an antipattern from these normal errors is that like patterns these antipatterns are recurring throughout the code base. In my recent experience in dealing with performance issues, I had observed certain recurrent themes that are undermining the overall application performance. Most of these antipatterns are well documented but it seems we do not learn from others mistakes. We need to make our own mistakes. I am recounting some of the common patterns that I observed in the recent months.

Recently, there was a major fire outage reported. The building maintenance team informed the fire brigade department. The fire brigade came in, helped douse the fire and tried to salvage whatever they could. The owner of the building demanded an independent assessment of the reasons behind the fire, what triggered it and how to make sure this does not happen again. The building maintenance team called in an independent assessment team and asked them to comb the carnage and find out what might have caused this!

The independent assessment team went through the motions of accumulating the evidence, looking for telltale signs of what might have gone wrong and then eventually did an event reconstruction on how events would have unfolded on that day. Subsequently, the team came out with the recommendations that need to be implemented to make sure that such an outage does not happen again.

How many times, we have seen that one of the easiest way of cleaning up your mail box is to delete all the enterprise announcements and group e-mails? Are we getting bombarded with too many policy change mails, group emails and announcements? After a few days of the email bombardment, are our brain gets conditioned to just ignore them ?

All this leads to a point where we start becoming clueless about

• Happenings in the Enterprise
• Policy/Process Changes that might be affecting us

which means we might be working harder and not smarter.