Big Data is taking the world by storm. With the huge amounts of data emanating from various digital sources the importance of analytics has tremendously grown making the companies to tap the dark data that was considered useless all these years. As the companies are bound to provide results on the fly the importance of big data has proliferated across the industries at a swift pace.
According to Gartner, Big Data is comprised of high velocity, high volume, and high variety data, which he calls 3V’s
- Velocity – Denotes the speed at which data is emanating and changes are occurring between the diverse data sets.
- Volume – Around 6 million people are using the digital media and it is estimated that about 2.5 quintillion bytes of data is being generated every day.
- Variety – Most of the data is unstructured in nature.
- Veracity – 27% of businesses are not sure if the data they are working on is accurate.
Some of the industries propelled by big data analytics are –
Big Data Contributions to Healthcare
The level of data generated within healthcare systems is not trivial. Traditionally, the health care industry lagged in using Big Data, because of limited ability to standardize and consolidate data.
But now Big data analytics have improved healthcare by providing personalized medicine and prescriptive analytics. Researchers are mining the data to see what treatments are more effective for particular conditions, identify patterns related to drug side effects, and gains other important information that can help patients and reduce costs.
With the added adoption of mHealth, eHealth and wearable technologies the volume of data is increasing at an exponential rate. This includes electronic health record data, imaging data, patient generated data, sensor data, and other forms of data.
By mapping healthcare data with geographical data sets, it’s possible to predict disease that will escalate in specific areas. Based of predictions, it’s easier to strategize diagnostics and plan for stocking serums and vaccines.
Big Data Applications: Manufacturing
Predictive manufacturing provides near-zero downtime and transparency. It requires an enormous amount of data and advanced prediction tools for a systematic process of data into useful information.
Major benefits of using Big Data applications in manufacturing industry are:
- Product quality and defects tracking
- Supply planning
- Manufacturing process defect tracking
- Output forecasting
- Increasing energy efficiency
- Testing and simulation of new manufacturing processes
- Support for mass-customization of manufacturing
Big Data Contributions to Public Sector
In the public sectors, the major confrontations are the amalgamation and ability of the big data from corner to corner of various public sector units and allied unions. Big data provides a large range of facilities to the government sectors including the power investigation, deceit recognition, fitness interconnected exploration, economic promotion investigation and ecological fortification.
Big data is even used to examine the food based infections by the FDA. Big data results are fast which outputs to quicker well-being. Also in the investigation of a huge volume of communal complaints uses the big data analytics. This same analytics are utilized in the course of health check statistics in urgency and resourcefully for quicker pronouncement manufacture and to become aware of mistrustful or falsified declarations.
Big Data Applications: Media & Entertainment
Various companies in the media and entertainment industry are facing new business models, for the way they – create, market and distribute their content. This is happening because of current consumer’s search and the requirement of accessing content anywhere, any time, on any device.
Big Data provides actionable points of information about millions of individuals. Now, publishing environments are tailoring advertisements and content to appeal consumers. These insights are gathered through various data-mining activities. Big Data applications benefits media and entertainment industry by:
- Predicting what the audience wants
- Scheduling optimization
- Increasing acquisition and retention
- Ad targeting
- Content monetization and new product development
Big Data Contributions to Learning
Big data has great influence in the education world too. Today almost every course of learning is present online. Along with the online learning, there are many examples of the use of big data in the education industry. Applications named as the Bubble Score allow teachers to convey multiple-choice assessments through mobile devices and notch up paper tests through the cameras of the mobile phones. Equipment like this usually assists teachers to send out the outputs to rank books and trail development all along distinct characteristics.
Adaptive learning : Further than just reformation coursework and the grading development, data-driven classrooms opened up the understanding of what children learn when they study it and to what height. Enterprises produce digital courses that use big-data-fuelled prognostic analytics to locate what a learner is learning and what components of a lecture plan most excellently ensembles them at those situations.
Problem control : Sometimes, a student submits his friend’s homework instead of his own. In that situation, instead of getting the punishment he gets appreciation and the other innocent student gets the punishment. So in these situations, big data entertains the cross checks of the assignments in order to find out whose writing matches with the assignment’s writing.
Big data has also played an important role in crime detection. Understand the role of Big data in crime detecction. For real life uses cases of Big Data , go through Big Data use cases – real life case studies.