The complexity of the world is increasing exponentially, and education is seen as the key to become a successful citizen. However, many educational institutes struggle to arm students with the necessary requirements to excel. Combined with rising tuition and shrinking funding, obtaining a quality education is not an easy task. It is extremely important to find the ways to offer high quality education at affordable cost. Modern analytics can provide efficient ways to improve student enrollment, student performance, and quality of in-class education.
With the increase in popularity of online education, the amount of data that is collected relating to student progress and learning patterns and habits increases. This kind of incremental information gives a more accurate picture of the learning process with respect to traditional learning methods. This data can be used along with modern analytical concepts to improve and personalize online learning for students.
Massive amounts of medical data are generated every day from various healthcare organizations such as payers, providers, and pharmaceuticals. This data includes valuable information to significantly improve the quality and reduce the cost of healthcare.
However, the size and the complexity of these datasets present great challenges in analyzing and extracting correct insights to achieve industrial goals. Modern analytics provides capabilities to get full advantage of big data by avoiding unexpected pitfalls and roadblocks.
Manufacturing has been dramatically improved with waste reduction and variability of production processes using lean and six sigma methodologies. The quality and yield of products are significantly improved, giving manufacturers advantage to win today’s highly competitive market.
Modern analytics can make this an even bigger success by uncovering hidden insights and streamline manufacturing value chains by searching for core determinants of process improvement. Furthermore, modern analytics can help manufacturers to identify hidden patterns and relationships among variables and optimize the factors that have greatest effect on product yield.
With new technologies, customers are always changing the way they research, interact, and shop for products, and services. Retailers must adapt to this new environment and find meaningful ways to connect with their customers efficiently and effectively.
Modern analytics helps retailers to obtain a comprehensive understanding of market sectors, customer segments, products, distribution channels, competitors, and employees to leverage their businesses.
Data science and machine-learning algorithms are transforming the big data community. While this growth is seen in almost every industry, the one that may be affected the most is telecommunications.
With rich datasets about customer preferences and behaviors, there is a huge opportunity for industries to use data science by gathering, aggregating, storing, and analyzing these trillions of bytes of customer likes and dislikes. Analytics can be used to enhance loyalty and to provide a truly tailored brand experience that customers are demanding.
The Fashion industry is a very dynamic industry. It generates good amounts of data across procurement, production, sales, and distribution. This data provides a good opportunity for clothing manufacturers to find novel ways to engage with their suppliers and clothing retailers to engage with their customers and provide maximum quality product and services while still increasing profits and revenue.
Advanced analytics provides ways to reduce material cost, manufacturing cost, and distribution cost for clothing manufacturers and improve sales for clothing retailers by using comprehensive analyses on procurement, production, distribution, customer behavior, and customer spending patterns.