Data mining is a powerful new technology which is helping enterprises to turn data and information into knowledge. Modern day businesses handle and process humongous amounts of data, which can be gathered either in-house or from external sources.
With the advent of the Internet, web, and mobile devices, the main challenge of the decade is to manage this huge resource of unstructured or raw data, which is getting generated every moment at a very fast pace. Unstructured data streams rapidly and constantly from different sources and is heterogeneous and variable in format. Unstructured data comprise of all data flowing in from customer interactions on websites, marketing applications running on websites, social networks, e-commerce sites, blogs, and responses from surveys and feedback. These data can be dug into and used to uncover customer consumption patterns, product and brand preferences, and other information which queries and reports can’t effectively reveal. So even with an investment of time and money, it is necessary to handle and harness this huge volume of data efficiently, and this is what has given rise to the importance of data mining.
How Big is This Data Volume?
The amount of raw data stored in corporate databases is exploding and rising exponentially over the years. When we refer to huge amounts of data or Big Data, can you imagine what volume of data are we talking about? Databases are now measured in gigabytes and terabytes, where one terabyte = one trillion bytes. Data can also be in petabytes, where 1 petabyte = 1,024 terabytes.
What is Data Mining?
Data mining, or knowledge discovery, is the computer-assisted process of using appropriate tools and procedures to analyze the massive data sets and extract meaning and patterns from them. Data mining tools predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that are otherwise time-consuming and they scour databases very quickly to find hidden patterns and predictive information that experts may find difficult to find and foresee.
Data mining derives its name from the similarities between searching for valuable information in a large database and mining a mountain for valuable ore. Both processes require sifting through an immense amount of material, efficiently and intelligently to discover where the real value lies.
How is Data Mining Used?
Though data mining is still in its infancy, companies in a wide-range of industries, including retail, finance, healthcare, manufacturing, transportation, and aerospace are already using data mining tools and techniques to take advantage of historical data. By using pattern recognition technologies and statistical and mathematical techniques to sift through the warehoused information, data mining helps analysts recognize significant facts, relationships, trends, patterns, exceptions and anomalies that might otherwise go unnoticed. These patterns and relationships discovered in the data help enterprises to make better business decisions, identify sales and consumer trends, design marketing campaigns, predict customer loyalty, and so on. Data mining can be used by a company to unearth the following trends and information:
- Consumer consumption pattern: Identify the common characteristics and patterns of customers who buy certain products from certain companies.
- Customer churn: Differentiate between loyal customers and customers who are likely to shift their brand and buying preferences.
- Fraud detection: Identify transactions more likely to be fraudulent.
- Direct marketing: Generate mailing list based on the prospects that are more likely to have a better response rate.
- Interactive marketing: Decipher how to improve applications and features of the company’s website to make it more interactive hold more attention of the visitor.
- Market basket analysis: Understand what products or services are commonly purchased together.
- Trend analysis after a marketing campaign: Reveal the impact of a particular marketing campaign and if there was any change in sales figures and trend.
How Data is Mined – The Tools and Methods
Data mining tells you important things you didn’t know or helps you to visualize the future pattern and trend. The technique that is used for the automated extraction of patterns is called modeling. Modeling is the process of building a model or a set of mathematical relationships and algorithms based on data from situations where the answer is known and then applying the model to other situations where the answers are not known.
Here are some of the commonly used data mining tools and methods:
- Traditional Data Mining Tools: These are data mining programs and software which help companies establish data patterns and trends by using a number of complex algorithms and techniques. Some of these tools analyze in-house data while others process external data.
- Dashboards: These are programs are installed in computers to monitor information in a database. They reflect data changes and display them in the form of charts or tables, enabling the company to see how the business is performing. Historical data also can be used, so that the company can identify the trend change and identify the cause and effect factors.
- Text-mining Tools: This tool is used to mine data from different kinds of text, ranging from Microsoft Word and Acrobat PDF documents, emails to simple text files. These tools scan content and convert the selected text into a format that is compatible with the tool’s database. The data captured from the textual formats can be a wealth of information which can be mined to discover trends, concepts, and attitudes.
Besides these tools, other applications and programs may be used for data mining purposes.
For present day organizations, data goes hand-in-hand with inventory, labor, and capital. Companies need to effectively capture, visualize, analyze, and apply the inferences from the analysis of data collected from various sources. This will help them stay ahead of their competitors, formulate business strategies, envisage the future market trend, and as a result increase their operational efficiency, profits, sales volume. So data mining is the buzzword now and will continue to be a topic of increasing importance down the years.