Analytics is the systematic mathematical analysis of statistics or data. It’s used for the scientific discovery, interpretation, and then communication of useful trends in data sets. It also involves applying statistical data patterns toward effective decision making. Analytics relies on several models including: The neural network (network) The data analysis models are also called the big data, due to their large amount of relevant data, and the large number of nodes (data sets) used in the analysis. Inference engines (or neural-networks) are based on various mathematical models including logistic, neural, decision trees, decision caffeinator etc.
Data analytics focuses on the study of customer behavior, to provide information about customer preferences and purchasing behaviors. It helps companies to provide targeted promotional and marketing communications that increase sales and drive business growth. Some of the applications of data analytics are: E-mail marketing, direct response, event marketing, lead generation, market research, product catalogues etc. Data mining is a technique used to extract and analyze large sets of unstructured or semi-structured data for a given purpose, such as business intelligence, customer management, marketing etc.
Analytics makes use of rich information technology for extracting valuable insights from large volume of structured or unstructured data to solve complicated problems. This helps companies to take an informed decision. Data science is a field that combines mathematical programming with techniques of reasoning from large and complex data to provide recommendations.
Web analytics is a growing discipline that makes use of advanced technologies and sophisticated techniques to collect and analyze large sets of data from the web. It gives an up-to-date glimpse into how consumers use your products, how search engines rank sites etc. Web analytics can help predict the future behavior of your customers and improve your business performance by understanding where to target your promotions and which keywords and links will bring you more traffic. By providing real-time information about visitors to your site, web analytics can: Determine which web pages are most popular; Determine which keywords are used by your visitors; Determine which content on your web pages is the most attractive; Measure the number of times your website is clicked on and the amount of time it takes for a visitor to finish purchasing a product or service.
Data mining and web analytics provide better decisions by helping you to discover meaningful patterns from the massive amounts of unstructured data that is available to us everyday. These patterns can be used to target your advertisements better and increase your profits. Companies that have employed these methods have increased their revenue by hundreds of millions of dollars and helped to put an end to costly and inefficient efforts. Web analytics and data mining can help businesses to: Reduce operating costs by using better data-targeting techniques; Improve customer service and retention rates; Analyze and measure all forms of marketing including digital media, TV/ Films, Press, Outdoor activities etc; Improve productivity by enabling better decision making; Provide accurate and up-to-date statistical information. Many organizations have taken advantage of analytics and data mining to build better customer relations, reduce costs, enhance productivity and ultimately make better decisions.
Data mining and data analytics can be used in any business or organization to achieve specific goals. They provide organizations with actionable insights that can help them take strategic decisions. These insights can help you achieve your company’s goals by: Identifying prospects and opportunities; Measuring results; Making decisions; and Increasing company morale. A comprehensive integrated system that combines traditional statistics and new technologies, data mining and data analytics is necessary for organizations that want to stay on top. A high quality data analysis system combined with powerful tools that make analysis simple is the key to good decision making.
Analytics and data mining is not something that can be learnt overnight. It takes time to understand and properly implement the various steps involved. But it is worth the effort as the benefits far outweigh the drawbacks. When properly implemented and wisely planned, analytics and data mining can make a significant difference to your decision making process and improve the quality and accuracy of your data and information. A successful strategy requires a combination of creative insight from an analytics and data mining expert along with carefully developed and monitored operational processes. This requires considerable upfront investment but will reap tremendous benefits in the long term for your business.
Companies should make use of analytical techniques along with data mining to build better customer relations, reduce costs, enhance productivity, increase customer retention and improve profitability. By implementing these strategies along with the right analytics and data mining technology, organizations can reap the benefits of using innovative information science, technology and data analysis techniques. These technologies are the best means to deliver actionable insights. The right combination of these three powerful strategies can help you improve efficiency, quality and profitability.