Big data refers to the collection, analysis and implementation of massive data sets that are too large for traditional data-processing software. The goal of analytics is to extract meaningful, predictive and behavioral data in order to spot business trends and find meaningful insights into consumer and market behavior.
Once considered a fringe concept, big data has made major inroads into everyday business practices in recent years. According to research by Forrester, “40 percent of firms are implementing and expanding big data technology adoption. Another 30 percent are planning to adopt big data” in 2017.
New Trends in Big Data
Internet of Things: The Internet of Things (IoT) refers to the network of devices, appliances and other items that collect and exchange data through the internet. As millions of Americans purchase products such as the Amazon Echo, collecting and managing data from these devices will further push the limits of big data.
Edge Computing: Whereas traditional network models rely on a centralized data-processing center, edge computing processes data at the device level. The decentralized approach is a key feature of IoT technologies and allows smart devices to respond to data almost instantaneously, thus eliminating lag time. Self-driving cars, for instance, rely on edge computing. Without the use of a public or private cloud for data storage, the cutting-edge approach to computing allows for heightened security as well.
Quantum Computing: Recent advances in mathematics and science have moved quantum computing from theory to reality. Whereas traditional computers rely on the manipulation of bits (0s and 1s), quantum computers leverage physical phenomena (superposition, entanglement and interference) to perform calculations. The results allow companies like IBM and Apple to crunch billions of numbers at speeds once deemed unthinkable.
Advanced Analytics: Advanced analytics such as artificial intelligence (AI), deep learning and machine learning are some of the strongest drivers of big data. AI gained widespread attention with the 2015 rollout of RankBrain, Google’s algorithm for directing online search queries. RankBrain uses a cumulative learning process called “machine learning” to increase the accuracy of its online suggestions.
Intelligent Security: Cyberattacks are on the rise, according to a 2017 article in Financial Times which found that the number of security breaches has increased 27.4 percent since 2016. As a result, many companies are incorporating big data analytics in their security strategies through the use of firewalls, intrusion protection systems, user authentication and end-user training.
Benefits of an MBA With a Business Systems & Analytics Specialization
All managers need to keep abreast of these trends, and others, in the realm of big data. Managers should understand the power that is in the data and how it can be applied to decision making. They need to appreciate the tools and computing power that is available to them assess their business operation, analyze alternatives, and drive their strategies and operations.
The online MBA with a specialization in business systems and analytics from La Salle University covers the complex world of big data through courses in database design, data mining, business systems analysis and more. The online courses, taught by the same faculty found on campus, encourage students to apply advanced analytical tools through interactive courses that mimic real world scenarios. Each year brings new trends in big data. A forward-thinking MBA program is one way for future or current managers to stay ahead of the big data curve.
Learn more about the La Salle University online MBA program with a Business Systems & Analytics Specialization.