With Shrigb digging out money, following are top five indian states investments are happening:
Following are different kind of investments:
Talk about big data and things that appear first in an engineer’s mind is Hadoop & related technology. The key thing that is getting missed time and again by many developers’ working on Big Data is a sense of reading/understanding/learning the data and designing algorithms to achieve different objectives such as derivations, predictions etc.
Predictive Modelling
One of the key aspect of data science which is also key to Big Data is Predictive Modelling. I wanted to do some quick research and develop an understanding around this topic. However, while researching, it was found that the topic does include some complex underlying mathematical models which will surely be very hard to be understood by 80% of Software Engineers.
Lets try and understand basics of Predictive Modelling.
Predictive modelling is nothing but a process in which a model can be created/used to predict the probability of an outcome based on a set of input data. For example, lets take a very simple example. Companies do publish their plans to set up one or more plants/factories in a certain region. This can be simply used to predict that there are more jobs going to be created in that region. This prediction can be further used to predict money liquidity in that region leading to further investments of different sorts such as real estate, hospitals, schools etc. This data can be used by businesses to plan their investment in that region.
Recently, I have been working on a project where the objective is to come out with different models to predict growth in a region based on investments. Additionally, I have also been researching different models to predict company growth and next moves based on their past and present investments.
There are different models based on which predictive modelling is done. Some of the following is listed on wikipedia page which I shall be detailing out in due course of time:
Big Data know for four V’s is certainly a candidate for predictive modelling owing to the volume, variety, velocity & veracity of the data. For software service providers vouching to have expertise in Big data and not having expertise to play with data may not add lot of value to big data implementation projects.
If you are planning to buy one of those google glass device, be prepared to get google wallet account whether you like it or not.:-) This is because you may not be able to buy google glasses in other ways except by using google wallet. In addition to that, even if you are trying to gift the google glass to someone else, the recipient would require to have an account with google wallet for him/her to receive the support from Google.
To add to the above, a person owning a google glass device also needs to maintain his/her google wallet account to receive after sales support.
Google Glass
Google Wallet
The information can be further found in google glass terms and conditions page. Following is the screenshot.
Google Glass Terms & Conditions Excerpts
To me, this looks to be the Google strategy to kill two birds with one stone where, by doing good marketing of google glass, they are also going to propagate the widespread usage of google wallet. And, who knows in future, they also start charging cents for maintaining google wallet. Its about big money they are envisioning to make in future.
Personally, I am not a fan of using online wallets, be it google. However, this very clause of google glass terms and condition would only end up forcing me to use google wallet as I would surely like to try google glass device. Only time will tell if this would fly with a normal user and if google would have to relax on this term and condition in relation with “must-have” google wallet.
So, get a google wallet free with a google glass device!
Google glass performance
With google glass development, performance has to take center stage and software engineers, no more can afford to put performance testing on back burner. Following are some of the techniques for achieving high performance of glasswares:
Is it possible to predict the reusability index of a block of code in a standalone mode? Meaning, given no information about the code, and just the piece of code, would you be able to predict or tell if the code is highly reusable or not reusable at all?
Before going into this, lets understand the basic fundamentals in relation with code reusability.
One myth I have come across while discussing the code reusability is that code should be made reusable when demanded by requirements. For example, one says that for reusable services, one should write reusable components and thus, reusable piece of code. When asked to many people, I got the answer such as one may need to know more information to tell whether a block of code is reusable or not.
Reusability is very much related with cohesiveness of the code in a way that a block of code, high in cohesion, can be found to be highly reusable and likely to have less coupling or coupling which is based on well defined requirements. And, what can be termed as highly cohesive code? The block of code which adheres to the SOLID principle of Single Responsibility can be termed as code having high cohesion.
Thus, when you are given a standalone block of code, try to read the cohesiveness of the code. Meaning, try to find out if the block of code is serving just one functionality or serving multiple functionality. If you are able to find this, you may be able to determine the cohesiveness of the code. And code reusability is directly proportional to code cohesiveness.