Why Open Source is the Future of Big Data Analytics
We live in a technologically advanced society, a society where people from all age groups are connected together, use technology for their betterment and different day to day purposes.
Today we generate so much data that around 2.7 zettabyte of information is available over the internet. Accessibility to this data has provided a new face of technology and people, whose focus is shifted to data-driven business decisions and outcomes. For many businesses today, Big data is an evolving practice and profitable space for which there are continuous research, tool development and models to improve the existing system.
Big data analytics helps an organization use its data to unlock new opportunities and insights.It not only helps in cost reduction but also helps to achieve better and faster decision making. Companies use several big data technologies to get the most from their data. But these platforms and technologies are still kind of an enigma to people in the industry. To get ahead of the data and to get more out of it, companies are investing in the open source. And in 2019, we can see Big data has its future in Open Source technologies.
To give a small brief, open source big data analytics or open source technologies in big data analytics refer to the utilization of open source tools and software such as Apache Spark and Hadoop for analysis of data to gather useful insights. Organizations can then use these insights to make data-driven decisions to reach their business goals. Companies either use an entire open source software or various available open source tools for completing different tasks in their data analytics framework.
Gideon Mann, Bloomberg’s head of data science, told to datanami- “Open source has increasingly been a very important part of technology at Bloomberg”. “It’s just not possible to stay competitive without doing open source these days, so there’s a lot of open source that we leverage,” he added.
From a design thinking perspective, open source is a very desirable option which has added benefits of feasibility, solution desirability, and attainability. And the best part, it can deliver accurate real-time analysis on a huge volume of data with reduced data storage cost. One of the important factors for the growth of open source is that it allows several users in different areas to effectively work together. When companies share their knowledge in the community and allow others to contribute to it, the end result has new better possibilities and discoveries. If the companies had to tackle all the problems in the big data software on their own, without the help or involvement from the open source software then it will be really slow and solution very limited.
Mathias Gelbmann, Co-Founder of Solid IT talks about open source in one of his blog stating that- “We often see, that once Redis is installed for caching, and people experience its speed and reliability, they start moving more and more functionality there.” Redis is an open-source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.
One of the other reason for companies to adopt open source systems is the unavailability of data scientists. According to a study by McKinsey, there is a shortage of talent in the data science field at length. Companies want to expand their data science capability and its application but lack of talent is a big hurdle for them. Now open sourcing their data and technology help them to move forward with the market pace. These open source software don’t need expensive hardware as compared to major software companies which will push you to purchase a costly machine.
Mike Tuchen, a former Microsoft executive who is now CEO of big-data vendor Talend, told Inforworld in an interview, “ We expect the entire next-generation data platform will be open source.” “It’s the new normal,” he added. Talend, a big-data vendor claims big names such as GE, Citi, Lufthansa, Orange and Virgin Mobile as their customers.
Open source provides “try before you buy” concept, which is not only good for small company who don’t want to invest in complete big data paid softwares schemes, nevertheless it also provides a chance to try hand on experience with minimum risk. Apache family (i.e. Spark, Kafka, Hadoop, HBase, Tomcat, Flume, Flink and cassandra etc) is one of the biggest names in the Open Source which can be easily downloaded from the internet.
With the shortage of data scientists in the market, open source provide easy access to up-to-date solutions with low cost. On the top of that, open source market is growing and evolving rapidly than the proprietary softwares. Hence, its safe to say not only the future of big data is open source technology but it will be the greatest strength in data analytics.