Data collection is a crucial aspect in today’s world. A lot of data collected will be unstructured and requires processing to extract useful information into a practical form. A plethora of data mining tools are available which employ machine learning and artificial intelligence to extract data.
Data mining involves the process of mining and analyzing the data to extract usable information from it. This can provide quick solutions to your business needs which may otherwise have consumed a lot of time. Applications of data mining include market segmentation, fraud detection, trend analysis of the market, and a lot more.
Data mining is accomplished in numerous steps –
• Pre-processing: This is the first step in data mining, which refers to all the preliminary tasks that help in starting with the actual mining task. This step involves the removal of noise and anomalies from the data which needs to be mined. It also consists of filling values that are missing as well as normalizing the data with the use of aggregation and generalization techniques. During clustering, a huge set of data is partitioned into sub-classes.
• Classification: This involves the actual classification of data into defined categories. A lot of analysis techniques are employed for the identification of data elements and the relationship between data items within a set.
• Summarization: This offers a compact description of the entire data set.
Data mining is considered to be a combination of several techniques such as machine learning, statistics and pattern recognition. Data mining is a cumbersome task and requires the use of high precision tools for the purpose.
This tool is a component of the Oracle Advance Analytics which can provide excellent algorithms for data classification, regression, prediction, and specialized analytics. This is one of those Data collection tools which permit the analysts to target best customers and make better predictions. It as well helps in the detection of fraud as well as in the identification of cross-selling opportunities. The GUI of this miner is an extended version of the SQL developer offered by Oracle.
This is another reliable tool for data analytics and reporting. The key features of this tool are its ability to provide quick insights and rapid integrations. It offers unlimited data transformation patterns with graphs and attractive tables. This mining tool also permits data accessibility from various devices. This tool helps in placing data in the form of well-defined structures, thereby permitting easy processing of the data. The relational methods focus on business-critical matters as well as permit multi-dimensional analysis. The reports generated by this tool are reliable and eliminate the need for any additional software.
KEEL stands for Knowledge Extraction for Evolutionary Learning. This is an open source tool based on Java and is powered by an organized GUI. This permits the users to manage the data which are in different file formats. Data mining experiments can be carried out by installing JVM on the system. Various supported algorithms can be accessed by visiting the official website. This tool is ideal for educational and research purposes.
Although there are numerous data collection and mining tools are available, you need to look into the individual requirements of your business and then take a call to find out which one is the best for you. Research on the applications and the limitations of each tool and figure out which one would be the most suitable for you.