The transformative shift from a deterministic perspective to a probabilistic perspective laid the foundation for data analysis. Every company is looking out for opportunities to turn more profit, to maximize business metrics, and to do more for customers. As the amount of data available in digital form continues its exponential growth, analytics will be needed to help with smarter, faster data-based decision-making. Needless to say, business analytics has been adopted broadly across industries, organization sizes, and geographic regions. Even small business users are seeing the need for complex analysis, modeling, and predictions based on comprehensive sets of data. Analytics and data modeling tools can be applied on top of Big Data technology to extract meaningful trends and insights that can quickly deliver valuable business intelligence, agile visualizations, and advanced predictive analytics on any device or platform.

Internet and other technologies such as sensors have been able to measure many more activities, bringing about an explosion of data. Machine learning and cognitive computing are increasingly taking on bigger roles in businesses as machines can automatically learn from neural networks and have emotion detection capabilities. Mobile analytics is expected to make a rebound in the near future as today’s generation mostly used mobile tablets and phone for doing just about everything. Social media analytics is already being used widely by several organizations to review current trends or evaluate their marketing investment performance and to understand how to capture live social media trends and bubble up real-time alerts. Real-time analytics has gained momentum now-a-days by tracking systems, products, and equipment performance in real-time; quick decisions can be made that can greatly affect the efficiency of an entire organization.

Analytics is a multi-disciplinary activity; the value from insight comes not from the activity but from the execution. Farms are leveraging advanced analytics to provide more insight into when to plant, how to optimize crop yields, and when to harvest; manufacturers are turning to advanced analytics to predict when a machine on the production floor is going to fail so they can perform preventative maintenance before a failure causes expensive unscheduled downtime; financial services firms are leveraging the analytics tools to combat internal and external frauds; professional sports teams are using analytics for all manner of things, including the use of sensors on athletes to create optimized workouts and predict injuries.

The transformative shift from a deterministic perspective to a probabilistic perspective laid the foundation for data analysis. Every company is looking out for opportunities to turn more profit, to maximize business metrics, and to do more for customers. As the amount of data ....see more

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