Data mining is a powerful new technology with great potential to help companies focus on the most important information in the data they have collected about the behavior of their customers and potential customers. It discovers information within the data that queries and reports can’t effectively reveal. The amount of raw data stored in corporate databases is exploding. From trillions of point-of-sale transactions and credit card purchases to pixel-by-pixel images of galaxies, databases are now measured in gigabytes and terabytes. Raw data by itself, however, does not provide much information. In today’s fiercely competitive business environment, companies need to rapidly turn these terabytes of raw data into significant insights into their customers and markets to guide their marketing, investment. Data mining, or knowledge discovery, is the computer-assisted process of digging through and analyzing enormous sets of data and then extracting the meaning of the data. Data mining tools predict behaviors Continue reading
Data Management Concepts
Revenue Management in the Hospitality Industry
The revenue management refers to the application of business analytics methods to the consumer behavior at the micro-level and optimizes the product type, price and availability so that the revenue of the organization is maximized. The primary aim of revenue management is to assure that the right product is sold at the right moment to the right customer. The analytical methods are applied to understand the perception of the customers regarding the product value and using it to align with the price, availability and the placement of the product service. The business organization often faces questions regarding different consumer product such as how to sell them and when to sell them. The revenue management uses the data driven and analytical methods to maximize the organization’s revenue. The revenue management encompasses data mining and operational research so that the customer behavior can be identified and associated with the sales procedure of Continue reading
Data Warehousing – Meaning, Benefits and Implications
What is Data Warehousing? The term data warehouse or data warehousing was first coined by Bill Inmon in the year 1990 which was defined as a “warehouse which is subject-oriented, integrated, time variant and non-volatile collection of data in support of management’s decision making process”. When referring to data warehousing as subject oriented, it simply means that the process is giving information about a particular subject rather than the details regarding the on-going operations of the company. Moreover, when data warehousing was referred to as integrated it means that the data or information which are gathered from a number of sources are then all gathered to synthesize a coherent whole. On the other hand, data warehousing being time variant simply means that the data available were identified on a particular period. Lastly, data warehousing as being non-volatile means that the data is stable and when a new data is added Continue reading
What is Consumer Data Protection and Why is it Important?
Protecting consumer data is an important and necessary part of conducting business in today’s information society. Companies that fail to do so properly can lose consumer trust which can make a major impact on a company’s success as a business. Increasingly today, companies are more frequently making headlines for not taking the appropriate steps to protect consumer data. With huge payouts to customers, fines imposed by government counsels, and damaged reputations, enterprise-level companies must find ways to stay ahead of data thieves. Consumer data must be protected at all costs and implementing policies to do so are paramount to the success of enterprise-level companies. Consumers ultimately pay the price when a company fails to protect sensitive consumer data which can lead to loss of consumer trust in the company and a shift to a more capable company. The majority of businesses today do have a tight security strategy to protect themselves as Continue reading
The Role of Big Data in Marketing
Big data is large and complex data sets that are collected by companies and governments. The data that involve many types of information arriving in increasing volumes and with the incredibly fast rates. Big data signifies colossal volumes of data are being generated from assorted sources such as business processes, machines networks, and social media. Historically, it is a challenge to reserve the enormous volume of data, by the progression computing capacity that storage is not an issue anymore. Big data can be classified into three types of data which is structured data, unstructured data, and semi-structured data. The structured data being easily entered, processed, queried, stored and recover into a fixed format. The typical examples of structured data contain numbers and dates. The unstructured data cannot be fit or classified into a net box and the process and analysis are very hard and time-consuming. For instance, objects from blogs, Continue reading