What is Data Mining?

If there are questions that are unanswered by research, they will be answered by a strategy division, a data mining group, or someone else within the organization. We need to be more effective at collaborating with these groups.” Stephen Jin-Woo Kim.

Did You Know?

  • Data Mining is utilized in crime scenes.
  • It was used by the Los Angeles police department that enabled them to minimize theft activity by 33%.
  • Data Mining helps in predicting diseases.
  • With the increase in information, more and more data is entered enabling the medical field to move closer to the diagnosis.
  • There are too many Data Mining jobs.
  • Because of the shortage of trained and skilled professionals, there are a huge number of data mining jobs available across the globe.

The data mining industry is making great strides. Being a subset of Data Science, there is plenty of room available for candidates who wish to make a career in Data Mining/Data Science. The professionals with Data Science Certification enjoy preference by recruiters over the non-certified candidates.

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What is Data Mining?

Simply put, Data Mining is a process of turning raw data into useful information. Since every task in every organization revolves around data, mining the data and extracting the insights becomes the task of utmost importance.

Businesses use software to identify patterns in large batches of data, so that they can learn more about their customers in order to modify their strategies and make them more effective, minimizing costs along with improving sales.

Data mining relies on effective data collection, storage or warehousing, and processing.

Point to be noted

Data Mining processes are utilized to develop such machine learning models that power applications such as website recommendation programs and search engine technology.

Data mining can be used in spam email filtration, database marketing, fraud detection, credit risk management and even to perceive the opinion or emotion of users. Data Mining can be used by organizations for everything related to the interests of their customers, to the issues regarding their products, or spam filtration.

The process of Data Mining involves intensive warehousing along with potential computational techniques. Warehousing refers to the process where a company centralizes its data into one program or database.

Steps Involved in Data Mining

  1. Business Research

When you are required to implement a data mining process, a prior knowledge of the objectives of the business, resources available, and current scenarios is important. This is because it helps you chalk your plan of carrying out the mining process.
Once done with the specification of the project according to your business perspective, it can be formulated as a data mining plan, and you can create the preliminary plan for execution.

  1. Data collection and Preparation

The next step is to collect the data and explore it. When you observe the data carefully, you are able to determine how well it defines the business problem. So, you can conclude on what data is to be removed and what data should be added. Here you perform a quality check of the data and scan for patterns that are hidden in the data.

Then the data preparation is done, which includes tasks such as creating the case table to be used in building the model. So, the tasks you need to do are table, case, and selecting the attributes along with cleaning the data and transforming it.

Data cleaning involves selecting the data, cleaning, formatting, and arranging in a specified order.

  1. Data Transformation

There are five sub-steps involved in Data Transformation so that the data is transformed into final data sets.

  • Data Smoothing: involves noise removal from the data.
  • Data Summarizing: this involves the aggregation of data sets.
  • Data Generalization: the step that involves replacing low-level datasets with higher-level data concepts.
  • Data Normalization: in this step, the data is produced in sets.
  • Data Attribute Construction: the data sets are arranged in the set of attributes.
  1. Model Building and Evaluation

This phase requires you to choose and execute modeling techniques and calibrate the parameters to obtain optimal values. In primary model building, you are required to work with reduced data sets so that the final list has an optimal number of cases.

After building the model, you need to evaluate the model for aligning with business goals.

  1. Knowledge Deployment

Knowledge deployment refers to the process of using data mining within a target environment. This phase includes deriving insights and working information from the data.

The deployment includes scoring, the extraction of models, or integrating data mining models with data warehouse infrastructure, within applications, or querying and reporting tools.

What is a Data Mining Specialist?

A data mining specialist is clearly a professional involved with finding patterns and relationships within huge amounts of data to make future predictions and help businesses in making strategies. As a data mining specialist, you are able to turn into actionable insights that can help in minimizing costs, improving revenues, understanding consumer behavior, discovering new markets, so it can help in producing tailored market campaigns.

How to become a Data Mining Specialist

  1. Obtain your undergraduate degree

To become an expert data mining specialist, you are required to have a strong knowledge of Data Science. So, an undergraduate degree in computer science, data science, statistics, business administration, information systems, or any other relevant degree.

  1. Start your career as a Data Analyst

To initiate your journey to become a data mining specialist, you need to start with becoming a data analyst. This will enable you to hone the technical skills required for data mining, and you can understand the concepts of data extraction, collection, transformation, and loading deeply.

  1. Get certified in Data Science 
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This is of utmost importance, as you will require pursuing certification in Data Science to advance your career in this domain.

  1. Start your job as a Data Mining Specialist

With a relevant undergraduate degree and relevant experience in Data Science, you can start your career in Data Mining. The opportunities for data mining specialists can be found in many industries as in software corporations, and computer manufacturers, healthcare, finance, etc.

Final Thoughts

The average annual salary of a Data Mining Specialist can be around USD 62,225, according to PayScale. Also, the demand for data mining specialists is expected to increase by 20% by next year.

To make a career in this domain, the best way to go with an online training course that gives you amenities like flexible learning hours, learning at your own pace, selecting your preferred mode of learning. The doubt sessions are carried out by industry experts to ensure that you are prepared completely. You get career guidance as well.

Book your seat now!

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