Big Data and Analytics in Different Industries

Travel

The travel industry has always depended on treating statistics to provide the best possible service. Using data to predict when people will travel, where and how means companies can provide the exact service their customers need at the best time and at the right price.

For example, a flight company can use historical data collected on customer journeys to predict demand for fares in different periods of time so that they know when the demand is higher and when is lower. They can set different prices depending on the predicted demand for fares. Predictive analytics can help you dig down into even greater detail and give you the edge over competitors in a tight market.

Insurance

The insurance industry has always depended on math to calculate insurance costs. However, this usually depended on the history of the client in particular and other internal data sources.

For instance, travel insurance would be calculated on risk based on accidents statistics, probability of death and injury history. However, by using more powerful data analytics tools you can incorporate an even wider array of sources to build an even more specific picture of risk-related to one customer in particular.

Energy
The energy industry needs to find a constant balance between providing the right amount of energy. Too much and you lose profit, too little supply and your customers will find another provider fast.

Most power plants have a fairly good idea of when demand is higher and lower. This is no secret, but using data insights can help make energy provisions even more efficient and significantly cut costs. Again, by studying historical demand, power plants can predict minute-by-minute, hour-by-hour energy demands depending on anything from the season to time of day, then use this to provide the exact quantity of energy required.

 

Education
Education is an enormous market in the world. Education can actually use data to help them provide better and more appropriate education to students, although many of them have not noticed or started doing by this way.

When students move from one classroom to another and meet different teachers throughout the day, it can be hard to keep track of an individual student’s progress. However, numerous apps are using data collected in school to provide teachers with a more unified insight into their students’ academic progress and allow them to spot problems and provide additional support when needed.

 

Telecoms
Telecom companies have access to a huge amount of customer data, and so by using tools to analyze this they can provide even more personalized services that users actually want.

In the past, providing telecoms was relatively straightforward – you connected a customer to the network and allowed them to contact their friends, relatives and business associates. However, with the emergence of the Internet and ever more devices for communicating, telecom providers need to offer much more diversity in the services they offer. Data analytics can help them with this by segmenting the market ever more accurately and providing the exact deals different customers will want.

 

Finance
Finance is all about numbers, but complex algorithms help inform and support trading decision. Algorithms can collect data from an ever wider number of success. By using live and historical is find new opportunities faster than humans can read and discover, and to gain a competitive edge.

 

Retail
No industry embodies the basic elements of supply and demand better than retail. Data has always been used to understand how customers are buying, but data analytics will help this become even more accurate.

Internet of Things shelf scanners are increasingly able to tell stores how empty or full their stocks are. Data analytics will then allow stores to always provide the exact amounts of product needed.

Reference:

https://www.infragistics.com/community/blogs/mobileman/archive/2016/09/08/top-10-industries-benefiting-the-most-from-data-analytics.aspx