Database - Data Warehouse and Data Mining

Question: Discuss about "Database, Data Warehouse and Data Mining". Answer: Introduction Data Mining is the process of analyzing and categorizing the data in a number of different categories. The data is studies from various angles and a correlation is formed. It is used in a number of financial, marketing, retailing and other industries to determine the relationship between internal factors such as price, cost, inputs and the external factors such as profits, losses, customer satisfactions and feedback. Data warehousing lets business leaders sift through subsets of data and examine interrelated components that can help drive business. Looking at sales data over several years can help improve product development or tailor seasonal offerings. Data warehousing can also be used to look at the statistics of business processes including how they relate to one another. For instance, business owners can compare shipping times in different facilities to look at which processes and teams work most efficiently. Data warehousing also involves storing huge amounts of data in ways th at are beneficial to different divisions within the company. Databases are the structured sets of data that are present in a computer. Big Data and business intelligence Internet is loaded with huge volumes of data every single day and to manage this data with perfection is a task in itself. The buzzword in the technological world is Big Data. It refers to the massive volume of data which includes both the structured as well as the unstructured data. Organizations are now adapting Big Data as a technology in order to manage the huge volumes of data which is otherwise not possible with the traditional software and techniques [1]. Business Intelligence on the other hand is the set of tools and guidelines which converts a set of data in to meaningful information for the purpose of business and data analytics [2]. Advantages of Big data in data warehousing and data mining The basic aim of business intelligence is to optimize the processes that are involved in handling the information and achieve best possible results with improved customer satisfaction. This is brought in to application with the aid of Big Data. Big Data helps in figuring out the target customers and users. Predictive models are created and the inferences are made. Companies gather the data sets from the social media accounts, browser logs and other sources to gain an insight in to the general trends, practices and demands [3]. Optimization of business processes is another expertise of Big Data. Analysis of performance of the employees, creation of reporting, online analytics and processing are done with the help of this amazing technology. Other advantages of Big Data include: Cost Savings Hadoop is a tool that is used to implement Big Data and the use of the same can result in storage of data at a much lesser cost as compared to other techniques. Companies are therefore making use of tools such as Hadoop for the purpose of data warehousing rather than spending their cost in the expansion of data warehouse for storage and locating the data. After the data is stored successfully with the help of Hadoop, it is moved to the regular database that is used by the organization in order to analyze the data. Versatile big data tools can also function as multiple tools at once, saving organizations on the cost of needing to purchase more tools for the same tasks. Competitive Advantage Big Data allows its users to access the data easily which was difficult or next t impossible to access earlier. With the aid of such a capability to access the data from a number of different sources such as social media accounts, search engines, media streams and several more, companies can predict the demand for a particular product and can also implement and design clear marketing strategies. With these advantages, businesses are able to gain an edge on their competitors and act more quickly and decisively when compared to what rival organizations do. Needless to say, a business that effectively utilizes big data analytics tools will be much better prepared for the future than one that doesnt understand how important those tools are [4] New Business Opportunities New business opportunities can easily be approached and deduced with the help of Big Data. Advertising and marketing are the two sectors that have largely benefitted with the help of these processes. Add-on services, new services and real-time services are provided to the customers on the basis of the analysis done through Big Data and the business expands with the help of the same. In addition to those benefits, big data analytics can pinpoint new or potential audiences that have yet to be tapped by the enterprise. Finding whole new customer segments can lead to tremendous new value. These are just a few of the actionable insights made possible by available big data analytics tools. Whether an organization is looking to boost sales and marketing results, uncover new revenue opportunities, improve customer service, optimize operational efficiency, reduce risk, improve security, or drive other business results, big data insights can help [8]. Newer Databases NoSQL is the database that performs the Big Data Analytics with extreme ease. It provides rich visualization for creation of reports and documents that support the analytics results. It allows the flexible mode of exploration that is on the basis of various parameters such as time, geographical locations, revenues, quantities and many more. Predictive analysis with powerful and advanced algorithms such as classification, regression and exploration is also possible with the help of NoSQL [5] NoSQL data is the fabric that connects the more than 200,000 APIs (a number that continues to rise) in the world, each of which speaks the language of JSON or XML [6] It is an advanced database that promises consistency along with the scalability and supreme performance in the document and data storage and indexing [7] Conclusions Data Warehousing and Data Mining are the processes that work on huge volumes of data and can be successfully executed with the aid of Big Data. Business Intelligence is the major application area of Big Data and several techniques and tools have been developed for the same. In the present era, use of non-SQL databases namely NoSQL has increased which includes various databases under it. Bibliography [1] Jon Bakke, M. (2014). 5 big data implementation mistakes to avoid. VentureBeat. Retrieved 21 May 2016. [2] Google+., T. (2016). Business Intelligence | Information Builders. Informationbuilders.com. [3] How is Big Data Used in Practice? 10 Use Cases Everyone Must Read. (2016). [4] Big Data Use Cases | Qubole. (2016). Qubole. Retrieved 21 May 2016. [5] Pentaho and NoSQL Databases. (2016). Pentaho. Retrieved 21 May 2016. [7] A deep dive into NoSQL: A complete list of NoSQL databases. (2014).. [8] Business Intelligence (BI) Overview of Major Components. (2016).