As we live in the fast-evolving world of information technology, we often hear the word “data mining” which is helping businesses making right decision for their business growth. However, many business owners still unaware about the importance of data and its significant role in business growth.

Therefore, this blog is dedicated to the majority of the businesses to empower them with the knowledge of data science.

What is data mining?

In simple word, data mining is the process of extracting the desirable data from the collection of data which is helpful for gaining the insightful knowledge and to make right decision for business optimization based on available customer’s data. It also helps acquiring new customers from the data visualization techniques.

Data mining is a synonym of the popular terms known as KDD which stands for knowledge discovery from data.

The data mining involves seven significant steps through which it discovers the knowledge required for the business for their decision-making process.

  1. Data Cleaning and integrations:

It removes inconsistent or noisy data from the collections of data sets.

At this initial stage multiple data sources such as from search engines, social media platform, spreadsheet and from various sources are combined together known as data integration.

2. Data selection and transformation.

After cleansing and integration of data the selection of relevant data is required from the database for its further analysis.

The selected data is then transformed and consolidated into an appropriate format or forms for performing aggregates of operation.

3. Data mining

At this stage, intelligent process with involvement of human, machines and software are implemented to extract desired data patterns

4. Pattern evaluation

Once the data is extracted, the data scientists and experts evaluate the desirable data pattern for the representation of the knowledge based on desirable measures.  

5. Knowledge presentation

At this stage the obtained data is ready for visualization for knowledge representation which is then shared with clients for the benefits of the business growth.

Techniques of Data Mining

Tools and Technologies of Data Mining

Data mining is a highly application-driven domain which require implementation of various tools and techniques to get the results. In Vmetasoft we use all of them to get the best outcome for the benefit of our business partners.

  1. Statistics Techniques

We use statistics technique for the collection, analysis, explanation and presentation of data. It is a set of rigorous mathematical functions that describe the behaviour of the object in a target class in term s of random and their associated probability distribution.

  • Machine Learning Model

We largely rely on machine learning model to classify and investigate the date from the data collection.

  • Supervised learning

It is the method in which the existing data is used, known as “Training Data Set”. The data then is being feed to the machine continuously in order for machine to understand the data with 97%-100% accuracy.

  • Unsupervised learning

It is a type of machine learning method in which cluster of unlabelled data feed to the machine. The machine recognizes the Familiar data out of unlabelled data from the “new training Data Set” and separates it from the data cluster.

  • Active learning

Active learning is a machine learning approach in which users play an active role in the learning process. An active learning approach can ask a user (e.g., a domain expert) to label an example, which may be from a set of unlabelled examples or synthesized by the learning program.

The goal is to optimize the model quality by actively acquiring knowledge from human users, given a constraint on how many examples they can be asked to label.

Other Machine learning model such as Decision Tree, KNN and Association Rule are applied for data mining process.

Why Data Mining?

We live in a world of information age where data means is everything, it is like an oil which boosted the industrialization in 18th century. For today’s fast-moving business and commerce, understanding data can help us analysing and measuring the estimated growth of our business against market completions.

Five reasons why your business need data mining:

  1. Customer Data:

As with data mining you can understand your prospective customers behaviour based on their purchase of a similar products and service from you or taken from market competitions.

2. Business offerings

Having appropriate customers data can help you identify required updated products and service, where you can also create a reminder about the existence of business to your busy customers.

3. Business growth

Data mining enable your business to visualize the pattern which is highly beneficial for your business to understand existing growth trends to increase your sales using right strategies.

4. Wining Market Completion

Every industry is crowded with competitors and when you have an advantage of data science your business will make an incremental progress in every process of your business.

With data with you can make right decision for implement new business strategies to confront new challenges of your rapidly industry.

5. Data Mining and Vmetasoft

Partnering with Vmetasoft to get started with modernizing data mining tools and techniques to become the leader of your industry. Our data scientists and engineers work relentlessly to help you discover the highly crucial information about your customer behavior, current market growth trends, analyzing social media platform, and high the demands of the volatile market place.

Get Started with Vmetasoft Data Scientists team today!

Contact Vmetasoft sales team now!