According to stats released by IBM, every day we generate more than 2 quintillion bytes of data. This data is produced from myriad sources including online shopping websites, smartphones, sensors, digital pictures and transaction records of online shopping and purchases, among others. In today’s scenario where data has become a basic necessity for every company, implementing big data technology and big data solutions has become equally important.
Basically, Leadership Consulting- The Need for Executive Search can be categorized into 3 different categories- structured data, semi-structured data AND unstructured data. According to a recent research report by NASSCOM, semi-structured data accounts for around 9% of the data that exists today. The other 81% goes into the account of unstructured data. Though big data technology came into play a couple of decades ago, it wasn’t embraced by every company.
When Apache came up with a new framework called ‘Hadoop’, it was when companies realized the importance of adopting big data solutions. From better decision-making to the improved results and better understanding of business strategies, Hadoop analyzes datasets and derive actionable insights. Leadership Consulting- The Need for Executive Search are using machine learning on Hadoop to lower costs of operation and to drive profitability.
There’s no denying that Hadoop has proved its value in the big data technology arena in numerous areas. From Leadership Consulting- The Need for Executive Search and NOAA to healthcare and insurance industry, big data technologies have become a necessary equation of the technology ecosystem. Hadoop is helping numerous companies like online shopping and retail giant Walmart by improving the operational efficiency. When online retailers dealing with online shopping are already looking for incorporating machine learning into their platform, it has become even important for the customers to know about big data.
Another software called Apache Mahout uses Hadoop platform in order to build the libraries of machine learning. By producing free implementations of scalable or distributed machine learning algorithms, it focuses on classification, clustering, and collaborative filtering. In addition to Hadoop, companies including online shopping websites, travel industry and crime branch among others are leveraging this software for future predictions to implement big data solutions in their respective industry.
There’s no doubt that implementation of Hadoop in any company can give protection to application and data processing against any kind of hardware failure and it has scalability, good processing speed, and high computing power. The negatives that it comes with include-
• Stability issues- Though iterations have been made in the versions of Hadoop several times, the issue of stability remains one of the major concerns.

• Vulnerability and Security- It doesn’t have encryption feature for networking and storing which leads to datasets being compromised.
• Compatibility issues- Installing anything from Hadoop requires a lot of effort due to improper act and mismanagement.
• Problems with Hive and Pig – Hive doesn’t entertain Pig’s UDFs and Pig does the same with Hive. Both of these cannot be used with each other.
• It is not appropriate for small datasets- Due to its high capacity design, it is not regarded as a suitable option for smaller businesses.
From online shopping websites to social media sites, big data is everywhere. And the big data technology and big data solutions are around too. Machine learning, AI, deep learning, supervised and unsupervised learning, among many others are helping big data to grow. But, make no mistake. With open-source frameworks like Hadoop using machine learning algorithms and statistics, organizations will have to enhance their IQ in Big data to increase productivity and reap benefits from it.