Data Analysis And Data Mining

One of the main functions of any business is to be able to use data to leverage a strategic competitive advantage. The use of relational databases is a necessity for contemporary organizations; however, data warehousing has become a strategic priority due to the enormous amounts of data that must be analyzed along with the varying sources from which data comes. Company gathers data by using Web analytics and operational systems, we must design a solution overview that incorporates data warehousing. The executive team needs to be clear about what data warehousing can provide the company.

Today we are doing a project report on Costco. For Sol and Robert Price in 1976 they asked friends and family to help out with an opening price of two point five millon to open Price Club on July twelfth, they open their shop in an air hanger on Boulevard in San Diego, California. They were originally going to serve only small business. Mr. Price found out that it will be more beneficial to serve select customers. Costco was founded by James Sinegal and Jeffery H. Brotman. Costco opened its doors in 1983 in Seattle, Washington. Price Club and Costco later merged and

Business Intelligence (BI) is the consolidation and analysis of internal data and / or external data for the purpose of effective decision-making. At the core of all BI initiatives is a data warehouse to hold the data and analytics software. The data warehouse stores data from operational systems in the organization and restructures it to enable queries and models to extract decision support reports.

An important measure of any database management system is how effectively related data can be collected, organized and presented as reports, and also for business intelligence. What techniques from data warehousing and data mining would be used to facilitate this.

The first true CRM system was not launched until the early 2000s. Technology made it easier to adopt CRM systems, and these systems became a common sight in retail stores. The goal of these systems was to analyze customer data with techniques like pattern recognition and data mining. With this information, management staff members could make informed decisions about business strategics, marketing and purchasing

As stated above, data mining is often used to solve business decision problems, “it provides ways to quantitatively measure what business users should already know qualitatively” (Linoff, 2004). A growing number of industries are using data mining to become more competitive in their market by primarily focusing on the customers; increasing their customer relationships and increasing customer acquisition.

These personnel could include front office, sales staff, and customer support and service. In each interaction opportunity with customers, CRM data is used by staff to produce rapid, informed, and, desirably, helpful decisions in order to both satisfy the customer in the present, and maintain their loyalty in the future. Though there are many approaches and techniques for CRM, all successful applications have three things in common. First, it is important to recognize that people are the most vital link between an organization and their customers. Second, the process of CRM must be tested and sophisticated, as well continuously improving. Third, there is usually a relatively large degree of technology integrated into the

Customer Relationship Management (CRM) software can help VTBC manage customer data to determine buying habits, coordinate its marketing strategy, forecast product sales, and interact quickly with customers. Vermont Teddy Bear Company’s marketing strategy is aimed at gift sales for Valentine’s Day, Mother’s Day, and Christmas. Their marketing strategy is ineffective during off peak times. Vermont Teddy Bear Company needs conduct market research and revise their marketing campaign to capture a broader customer base than just holiday gift shoppers. There is a need for a data warehouse to store the collected data and for data mining. Data mining can provide information on customer buying habits, trends and target potential

Design, code and deliver user friendly multi-tier business intelligence solutions that utilize data warehouse/data mining technologies to consume data across various database platforms and data stores.

Although data mining is still in its infancy, companies in a wide range of industries –

Generally, data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to increase revenue, cuts costs, or both. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases.

Data mining allows companies to focus on the more important information in their data warehouses. Data mining can be broken down into two major categories. Automated prediction of trends and behaviors, and automated discovery of previously unknown patterns. In the first category, data mining automates the process of finding predictive information in large databases. Questions that traditionally required exhaustive hands-on analysis can now be quickly answered directly from data. In the second category, data mining tools sweep through databases and identify previously hidden patterns in one step. This category is where the major focus of research has been on.

Today, customer relationship management is very important to the business world. Most of the companies established a department and the programs to manage their relationship with the customers. Customer relationship management (CRM) is a business strategy which designed to help a company to understand and look forward to the needs of its potential and current customers (Anderson & Stang, 2000). Customer data is being collected in several different areas of the company, stored in a central database, analyzed, and distributed to key points (Anderson & Stang, 2000).The business world once was “product-centric”, the companies just provided what they could produce. However, it is now become “customer-centric”, they provide products and service

Since higher education has blurred the lines with traditional businesses, it is important to have the tools to assist them with valuable data and information, in making decisions. Using of data and having the right data mining tools can insure the institute’s success, in many forms, such as, identifying market trends, precision marketing, new products, performance management, grants and funding management, student life cycle management and procurement to mention a few. To get a better grasp on these benefits it’s important to understand data warehouse, data mining and the associated benefits.

Data mining (sometimes called data or knowledge discovery) is the process of analyzing data from different perspectives and summarizing it into useful information - information that can be used to gain competitive advantage, improve processes, gain efficiency, save costs, utilizing and allocating resources optimally. Data mining tools not only analyze data from all perspectives, but also form relationships between seemingly random data into meaningful and actual information by finding correlations or patterns among dozens of fields in large relational databases which can be used to improve business and also gain intelligence which safeguard against