While big data is used in areas such as robotics, medicine, engineering, it can help us address a range of business activities from customer experience to analytics. Here are a few of them:

Product development

Companies like Netflix and Procter & Gamble use big data to estimate customer demand. They formulate predictive models for new products and services by classifying the key features of past and existing products or services and modeling the relationship between these features and the commercial success of offers. In addition, P&G uses data analysis with data from focus groups, social media, test markets and first store distribution to plan, produce and launch new products.

Predictive Maintenance

Factors that can predict mechanical failures, structural data such as the year, make and model of the equipment, as well as unstructured data including millions of log entries, sensor data, error messages and engine temperature, can be embedded in the data system. Thus, organizations applying the method of analyzing the problem indicators before possible problems can perform product maintenance more cost-effectively and maximize parts and equipment uptime.

Customer Experience

It is now possible to see the customer experience quite clearly. Big data allows you to collect data from social media, web visits, call logs and other data sources to enhance the interaction experience and maximize the value offered. Organizations can then provide personalized offers, reduce customer loss and proactively address issues.

Fraud and Obedience

When it comes to security, you’re not only confronted with a few bandit hackers, but with all the expert teams. Fortunately, security systems and compliance requirements are constantly evolving. Big data helps you to recognize patterns in data that compile aggregate information, with potentially dangerous data to make regulatory reporting much faster, and avoid potential problems.

Machine Learning

Machine learning is currently a very popular topic, and along with this popularity one of the main sources of developments in machine learning technology is of course big data. Now we can teach them how to use information, rather than planning them in length. The information obtained through the analysis of big data makes it easier for us to produce machine learning models and accelerate the learning process.

Operational Efficiency

Operational efficiency often does not have news value, but big data is most effective in this area. Using large data, it is possible to analyze and evaluate production, customer feedback and other factors to reduce interruptions in manufacturing and sales processes and to forecast future demands. Large data can also be used to improve and simplify decision-making based on current market demand.


Big data; It can help you innovate by examining the interdependence-relationship between people, institutions, assets, and processes, and then identifying new ways to use that information. Data forecasts can also be used to improve decisions on finance and planning. It is possible to determine which customers want to benefit from new products and new technologies through big data analysis. Determining dynamic prices for products through the data obtained depending on the conditions of the day is another opportunity that big data offers. The number of such facilities can of course be increased.