Data Mining at a glance
We are living in a world where data is driving decisions in every industry. Piles of data from various data points and sources are being considered crucial for any kind of business environment. Data mining is used a lot by companies and industries nowadays. According to Forbes, 53% of the companies have shifted towards data mining till December 2017 and this is likely to go up in the coming years. A large volume of raw data may seem to be of no use but with effective data mining processes, it is turned into useful data by identifying patterns among data clusters.
To stay in the market for as long as possible companies are adopting data mining and its tools. There are various domains that apply data mining techniques, this includes mobile service providers, retail sector, gaming, social media analysis, crime prevention, customer satisfaction, science and engineering and many more. Data mining is a vast field and has its practical applications in many fields and has the ability to grow any desired business even more. Each of the aforementioned fields requires data mining services in order to perform in a structured way.
Data mining tools and different software are used by firms to target their sales or to find the target audience. There are many techniques of data mining, including classification, association, outlier detection, etc. Among these, Predictive data modelling is used a lot to predict loyal customers and to make better business decisions. While analyzing the sales statistics, one can find which product requires attention and which product is performing excellently by using various data mining tools.
Data mining is the process of diving deeper into big data which is a large chunk of unstructured and unprocessed data. It has high potential and by providing the right methods for data parsing and management, we can acquire useful and reliable information that will enhance the capacity of the organizations.
Data mining meets the personalized requirements of users. For example, for business purposes, we can use data mining tools to discover patterns and relationships between raw data which will help in making smart business decisions. We can identify the trending products which are in high demand, and accordingly, we can plan our marketing stint. This helps to design and formulate better marketing strategies.
We don’t just take a large chunk of data and toss it into a data mining software. An overview of the variables that are being used is required. If the accuracy of our outcome is to be increased then more work and detailing are required. There are p-values and AIC that satisfy the statistics that predict data, also there is no need to practice false justification of statistics.
We use data mining to strengthen our business or organization and to make better decisions in the future based on predictive data modeling using data mining. The initial installation cost may be high at times but it is a step to improve the business standards and by gaining a foot ahead of others when it comes to competition in the marketing field. There are various tools for processing the big data, this includes the likes of Oracle Data Mining, Sisense, ReportMiner, etc. that help firms to facilitate their data spree. Let us take a look at top data mining applications in industries in 2019 which will give us a sense of capabilities and possibilities that the data mining possesses.
• Healthcare
Healthcare is one of the ever-growing sectors. There are always people out there with illnesses who are seeking wellness and that’s why data is always flowing at the health centres. With the proper parsing of data, we can find out which is the best course of treatment for a patient. A lot of anomalies happen during treatment, to reduce the mistakes data mining is used as a tool. It also helps in preventing wrong medication to a patient or to avoid contact with a harmful drug.
By using predictive analysis, we can find out which surgeon is best suited for a patient looking into their previous records where they have solved a medical case. We can use data mining in the healthcare industry to find out the purchasing habits of patients. It was not like that people didn’t work earlier, data mining has just made it easy and has extended the boundaries.
Parallel processing of data becomes easier and past records and treatments of a person can be easily looked and a new course of treatment can be set according to it which eventually helps the patient in better recovery. There are a lot of policies by the government to spread awareness about health insurance and there are a lot of people, to review all those documents is very tedious and time taking, but data mining can do it in no time giving us reliance on finding frauds.
• Customer Relationship Management
Every company wants to uplift themselves financially and morally and that’s why we have jobs like relationship managers. Customer relationship management and customer satisfaction are very important for a firm. When we don’t know about the customer or their preferences, we waste time trying to persuade him/her with the wrong choices. That is where data mining chips in, it gives us the necessary details about the habits of a customer in any desired field. With the help of this data, one can focus on the required topics and help the customer in a better way. What is the point of building a relationship with a person whom you don’t know in any way? Data mining finds out what is best suited for a client and helps in building better customer relationships.
• Fraud Detection
Millions are lost in fraud each day. You may hear about the scandals that shook the economy. It is insane to review all the paperwork by only manpower. Data mining reviews and validates the documents. And it finds the link between texts, the smallest detail somewhere else can give a hint of involvement of fraud. It connects all the related documents and detects whether it comes in the line of fraud or not. With a perfect algorithm that matches the documents, finance companies find out the loopholes in the system. The algorithm governs and validates using the rules and regulations pre-decided. When it comes to a consistent defaulter, predictive data mining process makes the job easy.
• Manufacturing Engineering
Manufacturing engineering inculcates all the fields of engineering in it. It is basically the conversion of raw materials into a furnished commodity in the most economical way. The quality of the product is also kept in mind. Data mining provides information about customer satisfaction regarding any particular product. One can analyze the client’s requirements and satisfaction and can find a way to improve their services. Data mining gives us the assumption of the reliability of any particular product.
Reviews and surveys help in finding major concerns and requirements of clients and according to that requirement specification, one can judge whether his work is going in the right way or not. Earthquakes are some common threats from which a building should be safe if it occurs. By using data mining, we can find out the exact number of calamities that happened in any particular area and the damage observed. Raw materials are looked thoroughly to provide best stability and endurance to a building. The best course of action is decided and repetition of mistakes in manufacturing is reduced.
• Structured Health Monitoring
Structural health monitoring is about making the buildings safer so it can stand against natural calamities. Constructors use data mining to look at the faults that might have occurred in the past and ensure not to repeat them. It helps in analyzing the area and gives us a prerequisite of threats or red alerts in that area. It also helps in gaining reviews from users and then working on the weak points accordingly. The Internet of Things also works in coordination with data mining and helps in the construction of structures that are safe for people living in it. It helps us in setting the right course for construction. It can also be used to determine which raw materials are best suited for which construction and threats can be managed well in advance. It creates a better world for all of us.
These examples of top data mining uses in industries in 2019 show how each and every government and non-government firms are trying their hands in the field of data mining to enhance their business capabilities and to make better decisions for the firm. Ranging from healthcare to finance, data mining is used to standardize processes and performances. It manages the enormous amount of unstructured data that is generated all over the world and finds scopes of utilising that.
“Data is wealth”. The immense potential of data mining and processing will increase manifold in the times to come but until that happens let’s ensure we are making the most of the existing system. Check out the Analytics program offered by Great Learning to find out how to build the key skills for the domain.
