With the Analytics industry showing increasing trends of using open source platforms for developing software, is it finally time to accept it as the next big thing that will take the industry forward? We take a look.
The analytics industry over the recent past has made progresses by leaps and bounds and that has got a lot to do with the way the world itself has progressed. Analytics is the detection, interpretation and communication of meaningful patterns in data. The advent of high speed internet, better connectivity and the general convergence of devices and technologies have forced corporations and industries to rethink their strategies, as far as business analytics goes. In fact analytical patterns now have evolved enough to understand the user browsing patterns and interfaces such that content to be displayed is tailor made for each individual browser. A great part of this change has been owing to the fact that the analytics industry has made way for open source to be an important part of its development.
MariaDB, one of the leaders in open source DBs, recently announced the release of its new big data analytics engine MariaDB Column Store. It is a columnar storage engine for parallel distributed query execution and data loading. Open Source unlike traditional closed source systems allows developers from across the globe to work on developing new software with a basic source code that is provided. It is, in many ways, a level platform where people are free to contribute their own bit as and when they please. The easy of usability is an important factor.
The diversity of the developers certainly brings a diversity of thoughts. That in turn helps to develop and design better analytical tools, keeping in mind the various types of audiences to which the product has to reach eventually. This integration of analytics helps companies to have a good idea about developing markets where they are making a foray into. More importantly it allows companies, industries, big data analytical firms, and think tanks to actually demonstrate their technical capabilities and prowess to the world.
Open Source can act as a low-cost effective marketing tool. When companies release all or a part of the product for the online developer community it attracts users and also brings in people who will help develop the product after seeing what it is capable of doing. Also the fact that open source packages are cheaper to produce and distribute enables them to become a low cost advertising technique for companies. In fact if companies release open-source codes, it helps to reduce the customer support costs because the users (usually developers) can figure out problems on their own. At the same time they can even come up with an optimum solution for the problem and it can be put out to all users for free.
Participating in open source developmental projects help to improve the employees’ working styles and makes for a hand on-the-job training regime. In fact it is also wrongly attributed or estimated that there is a loss of intellectual property once it is put in the open source market. That however is not the case. Open source projects, if anything, help bolster the company’s image as well as allow users to enhance the product rather than lose the intellectual rights over it. Also it is a great way to impress potential customers and employees. Companies can blog about their products and projects, develop partnerships for open source studies and can help create new features, fix bugs, provide software patches amongst others.
Also called Revolution Analytics, R, is one of the most widely used programs that is used by data scientists to analyze and solve their problems in various fields. Analytics based companies like Google, Facebook and others make use of this and it is important because not only do data scientists have every known data manipulation or statistical model at their fingertips, but also can create beautiful visualizations to help showcase their data. It also helps to get better results and since it is open source, it can work with the combined talents of data scientists from across the world.
How far do you think open source impacts the domain of analytics? Leave your comments below.
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