...1.0 Introduction Business analytics (BA) is the practice of iterative, methodical exploration of an organization’s data with emphasis on statistical analysis. It describes the skills, technologies, practices for continuous iterative exploration and investigation of past business performance to gain insight and drive business planning. Business analytics is used by companies committed to data-driven decision making. It focuses on developing new insights and understanding of business performance based on data and statistical methods. BA is used to gain insights that inform business decisions and can be used to automate and optimize business processes. Business analytics makes extensive use of statistical analysis, including explanatory and predictive modeling, and fact-based management to drive decision making. It is therefore closely related to management science. Analytics may be used as input for human decisions or may drive fully automated decisions. Data-driven companies treat their data as a corporate asset and leverage it for competitive advantage. Successful business analytics depends on data quality, skilled analysts who understand the technologies and the business and an organizational commitment to data-driven decision making. Once the business goal of the analysis is determined, an analysis methodology is selected and data is acquired to support the analysis. Data acquisition often involves extraction from one or more business systems, cleansing, and integration...
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...Top Data Management Terms to Know Fifteen essential definitions you need to know Fifteen Essential Data Management Terms We know it’s not always easy to keep up-to-date Contents with the latest data management terms. That’s why we have put together the top fifteen terms and definitions that you and your peers need to know. OLAP (online analytical processing) Star schema What is OLAP (online analytical processing) Fact table OLAP (online analytical processing) is computer processing that enables a Big data analytics Data modeling Ad hoc analysis user to easily and selectively extract and view data from different points of view. For example, a user can request that data be analyzed to display a spreadsheet showing all of a company's beach ball products sold in Florida in the month of July, compare revenue figures with those for the same products in September, and then see a comparison of other product sales in Data visualization Extract, transform, load (ETL) Florida in the same time period. To facilitate this kind of analysis, OLAP data is stored in a multidimensional database. Whereas a relational database can be thought of as two-dimensional, a multidimensional database considers each data attribute (such as product, geographic sales region, and time Association rules (in data mining) Relational database period) as a separate "dimension." OLAP software can locate the intersection of dimensions (all products sold in the...
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...Data Mining By: Holly Gildea CIS 500 Dr. Janet Durgin June 09, 2013 Data Mining We learn that data mining is a method of evaluating data from different viewpoints and summarizing it into useful information. Such information can be beneficial and used to increase things like revenue, and cutting costs, and so on. There are four categories that we will look at and determine the benefits for in regards to data mining: predictive analytics to understand the behavior of customers, associations discovery in products sold to customers, web mining to discover business intelligence from web customers, and clustering to find related customer information. To understand the behavior of customers by the use predictive analytics we must first understand what predictive analytics is. “Predictive analytics is the process of dealing with a variety of data and applying various mathematical formulas to discover the best decision for a given situation” (ArticleSnatch, 2011). This gives any business a competitive edge and helps to remove the guess work out of the decision making process therefore helping to find the right solution in a shorter amount of time. In order to find the solution faster there are a seven simple steps that must be worked thru first: what is the problem for the company, searching for multiple data resources, take the patterns that are observed from that data, creating a model that contains the problem and the data, categorize the data and find important...
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...In today’s business environment, businesses must be able to sift through and analyze massive amounts of data to gain a competitive edge over their competition. Utilizing data mining techniques, businesses are given the ability to analyze data from different points of view and turn it into useful information that can be used to increase revenue, cut costs, or both (Jason.Frand, n.d.). In today’s environment, competitive businesses use what is known as “Predictive Analytics” to perform mining and analysis of their data. In fact, predictive analytics is a form of data mining that if used properly can automatically sort and index a company database to create a predictive model based off corporate knowledge (Eric Siegel, 2005). Predictive Analytics use business intelligence technology to produce a score known as a predictor, which is a measurable value for every customer or organizational element. Once data records such as where, when, and how purchases are made are correlated, a predictive predictor or score is created. This predictor, in conjunction with other information, can assist in informing businesses what actions to take in order to get the consumer to purchase the goods they are offering. In fact, the proper utilization of predictive analytics can optimize marketing campaigns, improve web site behavior, reduce customer response times, increase revenue, and cut costs. The way companies and customers interact and perform their daily business has changed throughout the years...
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...Data Mining By Jamia Yant June 1st, 2012 Predictive Analytics and Customer Behavior “Predictive analysis is the decision science that removes guesswork out of the decision-making process and applies proven scientific guidelines to find right solution in the shortest time possible.” (Kaith, 2011) There are seven steps to Predictive Analytics: spot the business problem, explore various data sources, extract patterns from data, build a sample model using data and problem, Clarify data – find valuable factors – generate new variables, construct a predictive model using sampling and validate and deploy the model. By using this method, businesses can make fast decisions using vast amounts of data. There are three main benefits of predictive analytics: minimizing risk, indentifying fraud, and pursuing new sources of revenue. Being able to predict the risks involved with loan and credit origination, fraudulent insurance claims, and making predictions with regard to promotional offers and coupons are all examples of these benefits. It basically reduces the cost of making mistakes. This type of algorithm allows businesses to test all sorts of situations and scenarios it could take years to test in the real world. Studying customer behavior gives businesses a competitive advantage and allows them to stay ahead of the competition in their market place. Associations Discovery and Customer Purchases Association analysis is useful for discovering interesting relationships...
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...Data Mining Information Systems for Decision Making 10 December 2013 Abstract Data mining the next big thing in technology, if used properly it can give businesses the advance knowledge of when they are going to lose customers or make them happy. There are many benefits of data mining and it can be accomplished in different ways. The problem with data mining is that it is only as reliable as the data going in and the way it is handled. There are also privacy concerns with data mining. Keywords: data mining, benefits, privacy concerns Data Mining Benefits of Data Mining for a Business Data mining can be explained as the process of a business collecting data on their customers or potential customers to increase customer business. A business will collect data on their customers or potential customers and use that data to give them coupons, promote sells, and analyze buying and selling trends. Data mining can benefit the customer as well as the business. Data mining can be used in the retail industry, the finance industry, and the healthcare industry. Any industry can benefit from data mining but those are the top three (Turban & Volonino, 2011). Data mining is a way for large businesses to get to know their customers. The information gathered from data mining can let a large company learn what their customers want and how they want it. It can also benefit large companies get to know their employees, the company can learn how to satisfy their...
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...how can data warehousing, data mining & predictive analytics improve a business. Would it be applicable to all types of business or a particular business only? Information Technology develops rapidly, because changes in these technologies are making the people’s lives easier. There’s a growing need for information in market and the competition of handling information. Some businesses needs to improve their ability and capability to handle big data or information. Data warehousing evolved and plays a big or essential role in the storage, information management and to support strategic reporting and analytics of companies. Businesses are investing to integrate their daily operations to be contained in their data warehouse. Businesses aims for a growth to their competitive advantage compared to other organizations. Some of these competitive advantages includes data warehousing, data mining and predictive analytics to be applied with effective use of Information Technology. Data warehouse is designed to support decision making for leaders or owners of an organization. Data warehouse is truly important for which it gives or share all data by every department of an organization that allows decision making in order to achieve good analysis which will help better the organization’s business situation to improve their current operational processes. Data mining is a process that assists data warehouse to dig and analyze big sets of data and extracting the data. It allows...
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...Data Mining Jenna Walker Dr. Emmanuel Nyeanchi Information Systems Decision Making May 30, 2012 Abstract Businesses are utilizing techniques such as data mining to create a competitive advantage customer loyalty. Data mining allows business to analyze customer information, such as demographics and purchase history for a better understanding of what the customers need and what they will respond to. Data mining currently takes place in several industries, and will only become even more widespread as the benefits are endless. The purpose of this paper is to gain research and examine data mining, its benefits to businesses, and issues or concerns it will need to overcome. Real world case studies of how data mining is used will also be presented for a deeper understanding. This study will show that despite its disadvantages, data mining is an important step for a business to better understand its customers, and is the future of business marking and operational planning. Tools and Benefits of data mining Before examining the benefits of data mining, it is important to understand what data mining is exactly. Data mining is defined as “a process that uses statistical, mathematical, artificial intelligence, and machine-learning techniques to extract and identify useful information and subsequent knowledge from large databases, including data warehouses” (Turban & Volonino, 2011). The information identified using data mining includes patterns indicating trends...
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...Assignment 1: DDS, BI, Business Analytics, and Predictive Analytics LaShonda Spell Prof. S. Mirajkar CIS 356 Operating a successful business today involves utilizing the correct tools to make the best decisions for that business. The main tools that are used for making critical business decisions are DSS, DDS, BI, Business Analytics and Predictive Analytics systems. The concepts/ systems mentioned assist management in the major decision-making processes by providing crucial operational data in comprehensible formats for monitoring/ reviewing and analyzing. Making the best decisions regarding business operations determine the success or failure of the company and ensures that all business strategies are implemented and effective. In this essay, there is a brief overview of the similarities/ differences, methodologies/ technologies and evaluation of the capabilities of DDS, BI, Business Analytics and Predictive Analytics systems. Similarities and Differences among DDS, BI, Business Analytics, and Predictive Analytics regarding business scope/origins /histories/ methodologies/ technologies DDS (Data Distribution Service) are data communications based on the standards managed by the OMG (Object Management Group). The standards set by the OMG of DDS describe different latency levels of data communications for distributed applications (Twin Oaks Computing, Inc., 2011). DDS standard support data defining applications, dynamic publishing/ subscribing discovery and QoS policy...
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...Data Mining Raymond Greer Michael Falat, PHD Info-System Decision Making March 10, 2014 Determine the benefits of data mining to the business when employing. 1a. Determine the benefits of data mining to the business when employing predictive analytics to the understanding of the behavior of customers. Predictive analytics is area of statistical analysis that deals with extracting information from data and using it to predict future trends and behavior. (Bland-Thomas, Karen 2013) It gathers information from a variety of different methods such as: statistics, modeling, machine learning and data mining which is made of current and past information that is used to form future predictions of marketing campaigns and the profit of an organization. Predictive analytics has a four step process to collecting information: 1. Establishing objective: Establish what information that you what to gather, develop a thesis with experts and the data that is required. 2. Collecting good and high quality information: Establish a prediction from consumer’s social media opinions such as: emails, tweets, Facebook posts etc. 3. Understanding consumer’s behavior and intent: Understanding consumer’s behavior and their intent by predicting with organizational wisdom. 4. Predict action: Predicting a consumer’s next purchase at the correct offer and time. Using this method offers many advantages for organizations that realize the value within the enterprise data. Strategically...
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...Data mining is an iterative process of selecting, exploring and modeling large amounts of data to identify meaningful, logical patterns and relationships among key variables. Data mining is used to uncover trends, predict future events and assess the merits of various courses of action. When employing, predictive analytics and data mining can make marketing more efficient. There are many techniques and methods, including business intelligence data collection. Predictive analytics is using business intelligence data for forecasting and modeling. It is a way to use predictive analysis data to predict future patterns. It is used widely in the insurance, medical and credit industries. Assessment of credit, and assignment of a credit score is probably the most widely known use of predictive analytics. Using events of the past, managers are able to estimate the likelihood of future events. Data mining aids predictive analysis by providing a record of the past that can be analyzed and used to predict which customers are most likely to renew, purchase, or purchase related products and services. Business intelligence data mining is important to your marketing campaigns. Proper data mining algorithms and predictive modeling can narrow your target audience and allow you to tailor your ads to each online customer as he or she navigates your site. Your marketing team will have the opportunity to develop multiple advertisements based on the past clicks of your visitors. Predictive...
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...According to www.PredictiveAnalyticsWorld.com, “Predictive analytics is business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model, which has been trained over your data, learning from the experience of your organization. It continues to say, “Predictive analytics optimizes marketing campaigns and website behavior to increase customer responses, conversions and clicks, and to decrease churn. Each customer's predictive score informs actions to be taken with that customer.” Predictive analytics are used to determine the probable future outcome of an event or the likelihood of a situation occurring. It is the branch of data mining concerned with the prediction of future probabilities and trends. Predictive analytics are used to automatically analyze large amounts of data with different variables; it includes clustering, decision trees, market basket analysis, regression modeling, etc. There are three main benefits of predictive analytics: minimizing risk, identifying fraud, and pursuing new sources of revenue. Being able to predict the risks involved with loan and credit origination, fraudulent insurance claims, and making predictions with regard to promotional offers and coupons are all examples of these benefits. This type of algorithm allows businesses to test all sorts of situations and scenarios it could take years to test in the real world. Investing...
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...Data Mining Teresa M. Tidwell Dr. Sergey Samoilenko Information Systems for Decision Making September 2, 2012 Data Mining The use of data mining by companies assists them with identifying information and knowledge from databases and data warehouses that would be beneficial for the company. The information is often buried in databases, records, and files. With the use of tools such as queries and algorithms, companies can access data, analyze it, and use it to increase their profit. The benefits of using data mining, its reliability, and privacy concerns will be discussed. Benefits of Data Mining 1. Predictive Analytics: This type of analysis uses the customer’s data to make a specific model for the business. Existing information is used such as a customer’s recent purchases and their income, to create a prediction of future purchases and how much or what type of item would be purchased. The more variables used the more likely that the prediction will be correct. Such variables include the customer ranking, based on the number of and most recent purchases and the average profit made per customer purchase. Without data made available through web access and purchases by the customer, predictive analysis would be difficult to perform. The company, therefore, would not be able to plan nor predict how well they are performing. 2. Associations Discovery: This part of data mining helps the company to discover the “relationships hidden in larger data sets” (Pang-Ning...
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...Predictive Analytics in the Cloud James Taylor CEO, Decision Management Solutions Two important technology trends intersect to create opportunity for organizations ©2011 Decision Management Solutions Predictive Analytics in the Cloud “Innovation happens at the intersection of two or more different, yet similar, groups. Where one technology meets another, one discipline meets another, one department meets another.” Valdis Krebs, Founder & Chief Scientist, orgnet.com Predictive Analytics Cloud Contents: Introduction Pre-packaged Cloud Based Solutions Predictive Analytics for SaaS Predictive Analytics for On Premise Modeling with the Data Cloud Elastic Compute Power for Modeling 1 5 7 9 11 13 Predictive Analytics in the Cloud An Introduction “The challenge was to build a system that can sustain our consistent growth, scale when needed, predict performance trends, has high availability built in, and runs on the cloud.” Lenin Gali, Director of Business Intelligence at ShareThis “Everything we need to make a loan decision is right at our fingertips. It has definitely simplified operations and made life easier.” Beverly Pile, Vice President of Consumer Underwriting, Prosperity Bank Predictive analytics and cloud are hot topics in business today. Predictive analytics are increasingly the focus of many companies’ efforts to improve business performance with analytics while cloud is fast becoming the default option for purchasing and deploying...
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...Data Mining Professor Clifton Howell CIS500-Information Systems Decision Making March 7, 2014 Benefits of data mining to the businesses One of the benefits to data mining is the ability to utilize information that you have stored to predict the possibilities of consumer’s actions and needs to make better business decisions. We implement a business intelligence that will produce a predictive score for those consumers to determine these possibilities. Predictive analytics is the business intelligence technology that produces a predictive score for each customer or other organizational element. Assigning these predictive scores is the job of a predictive model which has, in turn, been trained over your data, learning from the experience of your organization. (Impact, 2014) The usefulness of predictive scoring is obvious. However, with no predictive model and no means to score your consumer, the possibility of gaining a competitive edge and revenue is also predictable. To discover consumer buying patterns from a transaction database, mining association rules are used to make better business decisions. However because users may only be interested in certain information from this database and do not want to invest a lot of time in searching for what they need, association discovery will assist in limiting the data to which only the end user needs. Association discovery will utilize algorithms to lessen the quantity of groupings of item sets or sequences in each customer...
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