Big data has become more popular among companies over the last few years, mostly due to the vast amount of data available from the IoT or Internet of Things, which offers valuable insights into the minds of their customers.
Because of this companies have put a high level of importance on the quality of their broadband connections and the hardware involved in bringing these connections into the workplace.
When analyzed correctly, data can be used to predict how well a certain product will do or even the likelihood that a particular soccer player will score a goal in his next game. Big data is becoming more important for a reason: it contains a wealth of information that, when properly utilized, can yield great results.
By collecting, assimilating, and analyzing the data’s content and then breaking it down into smaller pieces of intelligible information, big data can influence day-to-day decisions on the production and distribution of products and services. The results of any subsequent findings are often priceless and can help businesses reduce waste and costs, and increase their efficiency, productivity, and profits.
Take Italian-based tire manufacturer, Pirelli, for example. They took the help of SAP, a German-based company offering big data services, and equipped their inventory system with sensors in order to obtain consistent data. This led to a clearer picture of their waste management situation, and the data was able to pinpoint exactly what they needed to do to reduce their overall waste.
It is often a combination of small changes yielded from using data services that can have the biggest impact on companies, saving them thousands – even millions – of dollars in the long run.
With the help of big data services, companies and businesses can collect information in real-time. This real-time knowledge ultimately helps by providing faster solutions to any challenges that arise. This is especially important in nuclear power stations. By being able to diagnose problems instantly, measures can be taken to reduce waste and increase efficiency, and also help to prevent potentially catastrophic situations from arising.
Another example is the data storage units in IBM’s data centers. They produce an enormous amount of heat, and the facility requires consistent cooling in order to function at optimum levels. The company developed a mobile measurement technology, which monitors the temperature of storage units separately and cools them down when and where needed, as opposed to the more expensive method of cooling the whole plant at once. This reduced both energy consumption and overhead costs.
When it comes to businesses or any kind of organization, much of the inefficiency is created by a lack of communication and integration between different departments. Without transparency between departments, it can be difficult to spot areas that could have been improved had they been integrated in the first place.
Companies often have processes that operate in isolation without taking into account other processes, which can hinder efficiency and productivity. By integrating departments through the use of big data, this problem can be resolved.
For example, when Microsoft combined their heating and air conditioning systems into a single energy-efficient unit, this helped to reduce energy consumption and saved them a lot of money in the process.
One of the most valuable uses for big data is that it can assist companies in making accurate predictions for the future. This kind of information is priceless because it can identify and alleviate potential problems before they arise.
By gathering all the information available, big data systems can identify past and existing patterns and use those patterns to make accurate predictions by testing different hypothetical scenarios, i.e. a price increase on a specific part or service.
It essentially helps companies learn from history and provides the foresight of taking into account all kinds of outside influences and scenarios. Being prepared for these unexpected influences is a major tactical advantage when it comes to maintaining profits and providing a comprehensive picture.
The Los Angeles Police Department’s use of this technology is an unusual, yet brilliant example of how to reduce crime by analyzing big data. By working alongside a company called PredPol, they tweaked an algorithm that was originally used to predict earthquakes and fed it crime data instead. It can now accurately predict problem areas down to 500 feet, and as a result, there has been a drastically lowered rate of burglaries and violent crime in areas where they have implemented the technology.
The ways in which big data can change industries are endless. By modifying the way organizations and industries operate, big data is leading the world into a new age of precision and efficiency.