"Discuss Optimization Techniques Specific To Data Warehousing And Data Mining" Essays and Research Papers

  • Discuss Optimization Techniques Specific To Data Warehousing And Data Mining

     Data Warehousing and Data mining December, 9 2013 Data Mining and Data Warehousing Companies and organizations all over the world are blasting on the scene with data mining and data warehousing trying to keep an extreme competitive leg up on the competition. Always trying to improve the competiveness and the improvement of the business process is a key factor in expanding and strategically maintaining a higher standard for the most cost effective means...

    Business intelligence, Data mining, Data warehouse 1305  Words | 4  Pages

  • Data mining and warehousing

    Data mining and warehousing and its importance in the organization Data Mining Data mining 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...

    Data, Data analysis, Data mining 1341  Words | 5  Pages

  • Data Mining

    recent advancement of technical world, the concept of data mining, the extraction of hidden predictive information from large databases, is a powerful new technology with great potential to help companies focus on the most important information in their data warehouses. Data mining tools predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. The automated, prospective analyses offered by data mining move beyond the analyses of past events provided by...

    Data management, Data mining, Data warehouse 936  Words | 4  Pages

  • Data Mining

    Data Mining: What is Data Mining? Overview 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...

    Business intelligence, Data, Data analysis 1660  Words | 6  Pages

  • Data Mining

    Assignment : Data Mining Student : Mohamed Kamara Professor : Dr. Albert Chima Dominic Course : CIS 500- Information Systems for Decision Making Data : 06/11/2014 This report is an analysis of the benefits of data mining to business practices...

    Business intelligence, Customer, Data 2060  Words | 10  Pages

  • Data mining

    University CS 450 Data Mining, Fall 2014 Take-Home Test N#1 Date: September 22nd, 2014 Final deadline for submission September 29th, 2014 Weighting: 5% Total number of points: 100 Instructions: 1. Attempt all questions. 2. This is an individual test. No collaboration is permitted for assessment items. All submitted materials must be a result of your own work. Part I Question 1 [20 points] Discuss whether or not each of the following activities is a data mining task. •...

    Business intelligence, Customer relationship management, Data 1174  Words | 5  Pages

  • Data Mining

    SMS CUSAT Reading Material on Data Mining Anas AP & Alex Titty John • What is Data? Data is a collection of facts and information or unprocessed information. Example: Student names, Addresses, Phone Numbers etc. • What is a Database? A structured set of data held in a computer which is accessible in various ways. Example: Electronic Address Book, Phone Book. • What is a Data Warehouse? The electronic storage of large amount of data by business. Concept originated in...

    Data, Data mining, Data set 1453  Words | 6  Pages

  • Data Mining

    Chapter 1 Exercises 1. What is data mining? In your answer, address the following: Data mining refers to the process or method that extracts or \mines" interesting knowledge or patterns from large amounts of data. (a) Is it another hype? Data mining is not another hype. Instead, the need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. Thus, data mining can be viewed as the result of...

    Data, Data analysis, Data management 2055  Words | 6  Pages

  • Data Mining Techniques (Mini Project

    3. DATA MINING TECHNIQUES 3.1 NECESSITY OF DATA MINIING DATA Data is numbers or text which is a statement of a fact. It is unprocessed and stored in database for further analysis. Operational and transaction data such as cost and sales, is essential to modern enterprise's internal environment. Non-operational data such as competitors' sales and forecasting data, is responsible for analysis of external environment. INFORMATION Information is generated through data mining so that it becomes...

    Association rule learning, Cluster analysis, Computer 837  Words | 4  Pages

  • Data Mining

    Data Mining Assignment 4 Shauna N. Hines Dr. Progress Mtshali Info Syst Decision-Making December 7, 2012 Benefits of Data Mining 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, correlations...

    Business intelligence, Credit card fraud, Customer 1710  Words | 5  Pages

  • Data Mining

    Data mining is a concept that companies use to gain new customers or clients in an effort to make their business and profits grow. The ability to use data mining can result in the accrual of new customers by taking the new information and advertising to customers who are either not currently utilizing the business's product or also in winning additional customers that may be purchasing from the competitor. Generally, data are any “facts, numbers, or text that can be processed by a computer.” Today...

    Business intelligence, Data analysis, Data management 2354  Words | 7  Pages

  • Data Mining

    Data Mining Abdullah Alshawdhabi Coleman University Simply stated data mining refers to extracting or mining knowledge from large amounts of it. The term is actually a misnomer. Remember that the mining of gold from rocks or sand is referred to as gold mining rather than rock or sand mining. Thus, data mining should have been more appropriately named “knowledge mining from data,” which is unfortunately somewhat long. Knowledge mining, a shorter term, may not...

    Data, Data analysis, Data dredging 782  Words | 3  Pages

  • Data Mining

    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...

    Business intelligence, Chicken soup, Data 1921  Words | 6  Pages

  • Data Warehousing

    Data warehousing is the process of collecting data in raw form for analyzing trends. The benefits to data warehousing are improved end-user access, increased data consistency, various kinds of reports can be made from the data collected, gather the data in a common place from separate sources and additional documentation of data. Potential lower computing costs, increased productivity, end-users can query the database without using overhead of the operational systems and creates an infrastructure...

    Data mart, Data mining, Data warehouse 1687  Words | 5  Pages

  • Data Mining

    Data Mining 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...

    Business intelligence, Cluster analysis, Data 1603  Words | 5  Pages

  • Data Mining

     Data Mining Melody McIntosh Dr. Janet Durgin Information Systems for Decision Making December 8, 2013 Introduction 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 and future trends, allowing businesses to make proactive, knowledge- driven decisions Although data mining is still...

    Business intelligence, Cluster analysis, Data 2070  Words | 7  Pages

  • How Data Mining, Data Warehousing and On-line Transactional Databases are helping solve the Data Management predicament.

     How Data Mining, Data Warehousing and On-line Transactional Databases are helping solve the Data Management predicament. Robert Bialczak Walden University How Data Mining, Data Warehousing and On-line Transactional Databases are helping solve the Information Management predicament. Data in itself can be powerful, but also has many pitfalls if left to disparate databases and data collection routines. A collection of spreadsheets with account numbers entered into them can be view...

    Business intelligence, Data, Data management 853  Words | 3  Pages

  • Data Mining

    Data Mining On Medical Domain Smita Malik, Karishma Naik, Archa Ghodge, Shivani Gaunker Shree Rayeshwar Institute of Engineering & Information Technology Shiroda, Goa, India. Smilemalik777@gmail.com; naikkarishma39@gmail.com; archaghodge@gmail.com; shivanigaunker@gmail.com Abstract-The successful application of data mining in highly visible fields like retail, marketing & e-business have led to the popularity of its use in knowledge discovery in databases (KDD) in other industries...

    Business intelligence, Cluster analysis, Data 989  Words | 4  Pages

  • data mining

     Introduction to Data Mining Assignment 1 Ex1.1 what is data mining? (a) Is it another hype? Data mining is Knowledge extraction from data this need for data mining has arisen due to the wide availability of huge amounts of data and the imminent need for turning such data into useful information and knowledge. So, data mining definitely is not another hype it can be viewed as the result of the natural evolution of information technology. (b) Is it a simple transformation...

    Data, Data analysis, Data management 842  Words | 3  Pages

  • Data Mining for Business Decisions

    to create and operate data warehouses such as those described in the case? Do you see any disadvantages? Is there any reason that all companies shouldn’t use data warehousing technology? Information is the most important tool when making business decisions. As O’Brien and Marakas stated, “Today’s business enterprises cannot survive or succeed without quality data about their internal operations and external environment.” Companies that have large amounts of available data can use the information...

    Business, Business intelligence, Data 763  Words | 3  Pages

  • Data Mining

    Data Mining DeMarcus Montgomery Dr. Janet Durgin CIS 500 June 9, 2013 Determine the benefits of data mining to the businesses when employing 1. Predictive analytics to understand the behavior of customers 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, in turn been trained over your data, learning from the experience...

    Business intelligence, Customer relationship management, Data 1981  Words | 6  Pages

  • Data Warehousing and/or Business Intelligence

    chain management are major challenges because many foods have relatively short shelf life than other products. This article give me an example of how Coca Cola Japan Group, which is using advanced data warehousing techniques provided by Teradata , a hardware and software vendor specializing in data warehousing and analytic applications to improve the vending business. The article has three parts: The first part introduced Coca Cola Japan Group’s vending market faces new and increasing competition...

    Business intelligence, Caffeine, Coca-Cola 818  Words | 3  Pages

  • Data Warehousing

    Catholic University of Mozambique MIT 614 - Data Warehousing Assignment 1 This assignment is based on Topic 3 – Database Architecture Due Date: Friday, December 21, 2012 Name: Michael Bernardo Tomas Conje Fill in the blanks with the correct answers. 1) The two main Components of an Oracle Server are: Oracle Database & Oracle Instance. 2) The Instance consists of memory structures known as the System Global Area (SGA) and Oracle background processes. 3) A session is a connection between the...

    Cache, Computer software, Data hierarchy 374  Words | 2  Pages

  • Data Warehousing and Data Mining

    into the usage of data warehousing and data mining techniques to enhance the productivity of the business. The study of the processes is analysed so as to get the need of adaptation according to inherent demands of these industries in near future. The main topics we are discussing here are:   a) Data warehousing   b) Data Mining   c) ETL   d) Data Mart An attempt has been made to analyse different ways of using these for the enhancement in the different field. Data warehousing and current trends...

    Business intelligence, Data management, Data mining 348  Words | 2  Pages

  • Data Mining in Customer Acquisition

    Data mining can often help in finding the customer that gives the highest value to the company and using appropriate promotional tools to get to the customer. As the amount of data increases, the process of choosing relevant demographic would be troublesome without data mining techniques. Data mining helps the company in the following ways: 1. To differentiate and value customers and distribution partners 2. To determine the likelihood that a customer will purchase a specific ordering ...

    Consumer behaviour, Customer lifetime value, Customer service 1217  Words | 4  Pages

  • Data mining

    Data Mining Project – Dogs Race Prediction Motivation Gambling is very popular in the Republic of Ireland, weather is online or not, more people are joining gambling communities formed all over the Island of Ireland. The majority of these communities are involved in horse races related gambling and other sports, but there is a significant amount of people dedicated to dogs races. This is a multimillion Euro industry developed on-line and live or face to face. Objective There are many websites...

    1, 2, Data analysis 949  Words | 7  Pages

  • Analysis of Data Mining

    ITKM Analysis of Data Mining The article Data Mining by Christopher Clifton analyzed how different types of data mining techniques have been applied in crime detection and different outcomes. Moreover, the analysis proposed how the different data mining techniques can be used in detection of different form of frauds. The analysis gave the advantages and disadvantages of using data mining in different operation. The major advantage was that data mining enables analysis of large quantities...

    Cluster analysis, Credit card, Credit card fraud 842  Words | 3  Pages

  • Case Study: Active Data Warehousing

    1. Describe "active" data warehousing as it is applied at Continental Airlines. Does Continental apply active or real-time warehousing differently than this concept is normally described? An active data warehousing, or ADW, is a data warehouse implementation that supports near-time or near-real-time decision making. It is featured by event-driven actions that are triggered by a continuous stream of queries that are generated by people or applications regarding an organization or company against...

    Airline, Business intelligence, Continental Airlines 1485  Words | 5  Pages

  • Data Mining Soltions

    contains only three base cells: (1) (a1, b2, c3, d4; ..., d9, d10), (2) (a1, c2, b3, d4, ..., d9, d10), and (3) (b1, c2, b3, d4, ..., d9, d10), where a_i != b_i, b_i != c_i, etc. The measure of the cube is count. 1, How many nonempty cuboids will a full data cube contain? Answer: 210 = 1024 2, How many nonempty aggregate (i.e., non-base) cells will a full cube contain? Answer: There will be 3 ∗ 210 − 6 ∗ 27 − 3 = 2301 nonempty aggregate cells in the full cube. The number of cells overlapping twice is 27...

    Aggregate, Aggregate data, Computer 1720  Words | 5  Pages

  • Data Warehousing and Data Mining

    Data Warehouses and Data Marts: A Dynamic View file:///E|/FrontPage Webs/Content/EISWEB/DWDMDV.html Data Warehouses and Data Marts: A Dynamic View By Joseph M. Firestone, Ph.D. White Paper No. Three March 27, 1997 Patterns of Data Mart Development In the beginning, there were only the islands of information: the operational data stores and legacy systems that needed enterprise-wide integration; and the data warehouse: the solution to the problem of integration of diverse and often redundant...

    Data mart, Data mining, Data modeling 5149  Words | 16  Pages

  • DATA MINING (Presentation)

    ASKARI DANIYAL ARSHAD 2 OUTLINE DBMS DATA MINING APPLICATIONS RELATIONSHIP 3 DATA BASE MANAGEMENT SYSTEM A complete system used for managing digital databases that allow storage of data, maintenance of data and searching data. 4 DATA MINING  Also known as Knowledge discovery in databases (KDD).  Data mining consists of techniques to find out hidden pattern or unknown information within a large amount of raw data. 5 EXAMPLE An example to make it more...

    Cluster analysis, Data, Data analysis 714  Words | 17  Pages

  • 11 Steps to Successful Data Warehousing

    com/Articles.nsf/aid/BLACP01 11 Steps to Successful Data Warehousing Mining your corporate data for valuable customer information can improve your business performance. But it's not as simple as it sounds. By Phillip Blackwood There are 4 reader comments on this topic. Add yours! More and more companies are using data warehousing as a strategy tool to help them win new customers, develop new products, and lower costs. Searching through mountains of data generated by corporate transaction systems can...

    Data management, Data mining, Data warehouse 1938  Words | 7  Pages

  • Data Warehousing Assignment

    1. With necessary diagram explain about data warehouse development life cycle . Ans : Introduction to data warehouses. Data warehouse development lifecycle (Kimball’s approach) Q. 2. What is Metadata ? What is it’s uses in Data warehousing Archietechture ? Ans : In simple terms, meta data is information about data and is critical for not only the business user but also data warehouse administrators and developers. Without meta data, business users will be like tourists left...

    Business intelligence, Data management, Data mart 1833  Words | 13  Pages

  • Data Mining and Warehousing

    Summary: This is a thirteen that tells the reader all about Data Mining and Data Warehousing the evolution and the software's that are used and those that were used 10 years ago INTRODUCTION: The technology that exists with Data Mining and Warehousing is comparatively a new term but the technology is not. Data Mining is the process of digging or gathering information from various databases. This includes data from point of sales transactions, credit card purchases, online forms which are just a...

    Business intelligence, Data analysis, Data management 3173  Words | 9  Pages

  • Data Flow Diagram and Data Gathering Techniques

    of the Problem a. General Statement b. Specific Statement 3. Objective of the Study a. General Objective b. Specific Objective 4. Scope and Limitation of the Study 5. Significance of the Study 6. Motivation REVIEW OF RELATED LITERATURE AND STUDIES 1. Review of Related Literature 2. Review of Related Studies 3. Conceptual Framework 4. Operational Definition of Terms METHODOLOGY 1. Methods of Research 2. Data Gathering Techniques 3. Statistical Treatment of Data (optional) SYSTEM PRESENTATION A. Existing...

    Control flow diagram, Data flow diagram, Dataflow 1491  Words | 7  Pages

  • It Essay - Data Mining

    The Other Side of Data Mining Maral Aghazi – 500287851 November 10th,2012 ITM 200 Professor Roger De Peiza "As we and our students write messages, post on walls, send tweets, upload photos, share videos, and “like” various items online, we’re leaving identity trails composed of millions of bits of disparate data that corporations, in the name of targeted advertising and personalization, are using to track our every move” (McKee, 2011). Data mining has become extremely prevalent in today’s society...

    Data, Data analysis, Data mining 1998  Words | 5  Pages

  • Answers to Questions on Big Data

    companies unsure/skeptical on how to proceed with "Big Data"? Answer: Although organizations are increasingly becoming aware of the power that “Big Data” has or can bring, they are still unsure how to use it in their situation. They feel their organization is not ready. One of more of the three scenarios is possible. Companies may have a lot of data but they fail to read or decipher it correctly. Perhaps these companies invested in data warehousing and other such programs mindlessly without verying...

    Business intelligence, Data, Data analysis 1002  Words | 4  Pages

  • Data Warehousing

    Data Warehousing, Data Marts and Data Mining Data Marts A data mart is a subset of an organizational data store, usually oriented to a specific purpose or major data subject, that may be distributed to support business needs. Data marts are analytical data stores designed to focus on specific business functions for a specific community within an organization. Data marts are often derived from subsets of data in a data warehouse, though in the bottom-up data warehouse design methodology the data...

    Business intelligence, Data, Data analysis 6222  Words | 18  Pages

  • Data Mining for Business Intelligence

    Systems The goal of the term project is to develop a useful and viable prediction or classification model based on data. You will need to develop a research question, which you refine further based on the availability of data. You may need to merge multiple data sets together. Process: • Each team of 2 or 3 students will work on a business problem involving data analysis with real data. The project will focus on classification and prediction methods we covered during the semester. • A presentation...

    Data, Data set, Google 1123  Words | 4  Pages

  • Data Mining and Data Warehouse

    Information Systems Management Research Project ON Data Warehousing and Data Mining Submitted in Partial fulfilment of requirement of award of MBA degree of GGSIPU, New Delhi Submitted By: Swati Singhal (12015603911) Saba Afghan (11415603911) 2011-2013 ...

    Business intelligence, Data, Data analysis 2521  Words | 9  Pages

  • Dat Mining Annotated Bibliography

    Annotated Bibliography Data Mining Ayanso, A., & Yoogalingam, R. (2010). Profiling Retail Web Site Functionalities and Conversion Rates: A Cluster Analysis. International Journal of Electronic Commerce, 14(1), 79-113. doi:10.2753/JEC1086-4415140103 This article introduces the utilization of cluster analysis as a data mining tool. E-commerce has forced traditional businesses to reform their decision making processes and conduct its affairs based on activities occurring online. Monitoring...

    Business intelligence, Data, Data analysis 2553  Words | 7  Pages

  • Business: Artificial Neural Network and Data

    1. The independent data marts have inconsistent data definitions and different dimensions and measures, 2. Which of the following is not a major activity of OLAP? Analytics 3. Which of the following are reports that are similar to routine reports, Ad-hoc reports 4. Clustering techniques involves optimization this is because we want to create group that have maximum similarity among members within each group… 5. Which of the following is the reason why neural networks have been applied in business...

    Artificial intelligence, Artificial neural network, Artificial neuron 2021  Words | 7  Pages

  • data depth and optimization

    Data Depth and Optimization Komei Fukuda fukuda@ifor.math.ethz.ch Vera Rosta rosta@renyi.hu In this short article, we consider the notion of data depth which generalizes the median to higher dimensions. Our main objective is to present a snapshot of the data depth, several closely related notions, associated optimization problems and algorithms. In particular, we briefly touch on our recent approaches to compute the data depth using linear and integer optimization programming. Although...

    Algorithm, Computational complexity theory, Computational geometry 1546  Words | 5  Pages

  • Tic-Tac-Toe - Data Mining

    win is 60% and above.” Null Hypothesis “If X makes the first move then the probability of the player with X will win is less than 60%.” Data Collection and Preparation To prove or refute the hypothesis, data has to be collected. As we all know this step requires a great amount of time and effort. Also in order to build an effective model a data mining algorithm must be presented with a few hundred or few thousands relevant/applicable records. As mentioned above there are thousands of winning...

    Comma-separated values, Data, Data mining 1778  Words | 5  Pages

  • Data

    business. Two Security Vulnerabilities Hardware vulnerabilities. According to the network infrastructure diagram, we can see that there are 5 servers, 2 routers, 1 switcher, and 1 firewall. Each one of those servers is operate by a specific department, and all of those servers are connected to the main database server.The connection between each department’s server to the main database server take place without any access list or server, and that mean that any department’s user could...

    Access control, Active Directory, Computer security 1644  Words | 6  Pages

  • Marketing Big Data

    Introduction Big Data is indeed a better idea. Every day, we create 2.5 quintillion bytes of data–so much that 90% of the data in the world today has been created in the last two years alone. This data comes from everywhere: posts to social media sites, digital pictures and videos posted online, transaction records of online purchases, and from cell phone GPS signals to name a few. This data is big data. “Much like the scientific principle that we can’t observe a system without changing it, big data can’t...

    Business intelligence, Data, Data analysis 1864  Words | 6  Pages

  • Mining data management

    Troy Wilson* suggest a way for preserving and enhancing the value of exploration data E very year explorationists, industrywide, collect billions of dollars worth of data. Yet, when it comes time for geologists to extract value from their information, they often find that value has been lost through poor practices in data management. There is no reliable record of the data that has been collected or data is not where it should be - it has been misplaced or corrupted. Re-assembling information...

    Data, Data management, Kennecott Utah Copper 1595  Words | 7  Pages

  • GS 1140 A Look at Data Mining

    Your life? “A Look into Data Mining” Today with the ever growing use of computers in the world, information is constantly moving from one place to another. What is this information, who is it about, and who is using it will be discussed in the following paper. The collecting, interpreting, and determination of use of this information has come to be known as data mining. This term known as data mining has been around only for a short time but the actual collection of data has been happening for centuries...

    Bayes' theorem, Bayesian probability, Better 974  Words | 3  Pages

  • Data Mining Problems

    CIS 501: Information Systems for Managers Data Mining Problems Introduction Problem 1: Data-Based Decision Making Problem 2: Market Basket Analysis: Association Analysis Problem 3: Market Basket Analysis: Concept Tree/Sequence Analysis Problem 4: Decision Tree Problem 5: Clustering/Nearest Neighbor Classification Problem 6: Clustering             Problem 1: Data-Based Decision Making Supermarket Product Placement Suppose that we are responsible for managing product placement within a...

    Cognition, Data, Data analysis 1295  Words | 5  Pages

  • Data Gathering Techniques

    Data Gathering Techniques Data Gathering Techniques Interview • Interviews can be conducted in person or over the telephone. • Questions should be focused, clear, and encourage open-ended responses. • Interviews are mainly qualitative in nature. Data Gathering Techniques Advantages of interviews The main advantages of interviews are: • they are useful to obtain detailed information about personal feelings, perceptions and opinions • they allow more detailed questions to be asked • they usually...

    Evaluation methods, Interview, Qualitative research 886  Words | 21  Pages

  • Big Data

    A glimpse of Big Data Jan. 2013 What is big data? “Big data is not a precise term; rather it's a characterization of the never ending accumulation of all kinds of data, most of it unstructured. It describes data sets that are growing exponentially and that are too large, too raw or too unstructured for analysis using relational database techniques. Whether terabytes or petabytes, the precise amount is less the issue than where the data ends up and how it is used.”------Cite from EMC’s report...

    Business intelligence, Data, Data management 1900  Words | 6  Pages

  • Data Warehouses & Data Mining

    DATA WAREHOUSES & DATA MINING Term-Paper In Management Support System [pic] Submitted By: Submitted To: Chitransh Naman Anita Ma’am A22-JK903 Lecturer 10900100 MSS ABSTRACT :- Collection of integrated, subject-oriented, time-variant and non-volatile data in support of managements decision making process. Described as the "single point of truth", the "corporate memory", the sole historical register of virtually all transactions...

    Data, Data analysis, Data management 2771  Words | 13  Pages

  • Data Warehouse & Data Mining

    Chapter 1: Introduction to Data Mining 1.1 Introduction Generally, data mining is a process of analyzing data from different perspectives and summarizing it into useful information which that can be used as an input to the respective organisations for decision making and strategic planning. 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...

    Customer relationship management, Data, Data mining 4209  Words | 15  Pages

  • data

    Data Display Q no.1 Do you have a personal bank account? Bar chart Pie chart Q no.2 Your personal banking account… Bar chart Pie chart Q no.3 If you have a conventional banking account, the reason for this is that… Bar chart Pie chart Q no.4 Do you think Islamic banks are really Islamic (what is your perception)? Bar chart Pie chart Q no.5 Nowadays...

    Bank, Banking, Bar chart 261  Words | 3  Pages

  • DATA MANAGEMENT

    Topic 1: The Data Mining Process: Data mining is the process of analyzing data from different perceptions and summarizing it into useful evidence that can be used to increase revenue, cut 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. Association, Clustering, predictions and sequential patterns, decision trees and classification...

    Artificial intelligence, Artificial neural network, Data 887  Words | 3  Pages

  • Data Mining

    Question 1: Case One –eBay Q1.1. Discuss the relationships between business intelligence, data warehouse, data mining, text and web mining, and knowledge management. Justify and synthesis your answers/viewpoints with examples (e.g. eBay case) and findings from literature/articles. To understand the relationships between these terms, definition of each term should be illustrated. Firstly, business intelligence (BI) in most resource has been defined as a broad term that combines many tools and technologies...

    Business intelligence, Data, Data analysis 5812  Words | 17  Pages

  • Data Mining

    university CASE STUDY OF DATA MINING Summitted by Jatin Sharma Roll no -32. Reg. no 10802192 A case study in Data Warehousing and Data mining Using the SAS System. Data Warehouses The drop in price of data storage has given companies willing to make the investment a tremendous resource: Data about their customers...

    Business intelligence, Data, Data management 3792  Words | 14  Pages

  • Data Mining

    Contents Contents 2 The use of Data Mining and its applications in Retailing and Logistics 3 Introduction 3 What is Data Mining? 3 Data mining products used by retailing and logistics 6 General advantages of data mining and how they apply to logistics and retailing industry 7 General disadvantages of data mining and how they apply to logistics and retailing industry 9 Future trends/ enhancements 11 Conclusion 12 References 13 The use of Data Mining and its applications in Retailing...

    Business intelligence, Customer relationship management, Data 3287  Words | 9  Pages

  • Diamond in the Data Mine

    Diamond in the Data Mine by Gary Loveman The approach that Loveman used was highly effective outlining the importance of providing an exceptional customer service in today’s service industry through deep data mining. This article discussed 2 main points: * How Harrah’s Entertainment used information technologies to gather data about its customers and market effectively to them, in turn increasing their revenues in a competitive market. ...

    Casino, Casinos, Consultative selling 877  Words | 3  Pages

  • data analysis

    A Report On Data Warehousing Methods Information Technology Essay Todays Business world is highly dynamic and always changing, which makes it mandatory for every thriving company to create or sustain its competitive advantage. In order to be competitive, companies have to be receptive and nearer to its customers, for delivering value-added products and services in accurate time period. Companies also need to be able to maintain organizational information requirements faster and better than their...

    Business intelligence, Data management, Data mart 1643  Words | 5  Pages

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