a:4:{s:8:"template";s:5817:"<!DOCTYPE html>
<html class="no-js" lang="en-US">
<head>
<meta charset="utf-8"/>
<title>{{ keyword }}</title>
<link href="http://gmpg.org/xfn/11" rel="profile"/>

<meta content="width=device-width, initial-scale=1" name="viewport"/>

<style id="style-elastic-css" media="all" rel="stylesheet" type="text/css"></style>
<style id="theme-reset-css" media="all" rel="stylesheet" type="text/css">


a,
body,
div,
footer,
header,
html,
nav,
p,
section,
span,
ul {
  border: 0;
  margin: 0;
  padding: 0;
  font-size: 100%;
}

html,
body {
  height: 100%;
}

footer,
header,
nav,
section {

  display: block;
}



.clearfix:before,
.clearfix:after {
    content:"";
    display:table;
}
.clearfix:after {
    clear:both;
}
.clearfix {
    zoom:1; /* For IE 6/7 (trigger hasLayout) */
}
</style>
<style id="theme-main-style-css" media="all" rel="stylesheet" type="text/css"> 

body {
	color: #555;
	background-color:  #00C5FB;
	font: normal 100% Helvetica, Arial, sans-serif;
	line-height: 1.5em;
}
a {
	text-decoration: none;
	color: #e54b00;
	outline: none;
}
a:hover {
	color: #b73a00;
}
::-moz-selection {
	background: #ff5400;
	color: #FFF;
}
.last {
	margin-right: 0 !important;
}
header, footer, section, nav {  
   display: block;  
}
.container {
	width: 950px;
	margin: 0 auto;
	position: relative;
}

/* TYPO */

ul {
  list-style: disc;
}
p,
ul {
  margin-bottom: 20px;
}

/* # RTF
-------------------------------------*/
.rtf {
	font-size: 13px;
	line-height: 1.5em;
}

/* # HEADER
-------------------------------------*/
header {
	position: relative;
	z-index: 2000;
	background: #FFF;
}
#header-shadow {
	height: 8px;
	width: 100%;
	background: url() left -3px repeat-x;
	position: absolute;
	bottom: -8px;
	left: 0;
}
#header-content {
	padding: 14px 0;
	position: relative;
	margin: 0 auto;
}
/* LOGO */
#branding {
	float: left;
	margin: 0;
	font-size: 24px;
}
#site-title {
	margin: 0;
	line-height: 1em;
	float: left;
	margin: 0 15px 0 0;
	font-weight: normal;
	font-size: 1em;
	text-align: center;
}
#site-description {
	display: none;
	opacity: 0.75;
	font-size: 0.6em;
	line-height: 1em;
	float: left;
	padding: 0 0 0 15px;
	background: url() repeat-y;
	position: relative;
	top: 1px;
}
/* MENU */
#primary-menu-container{
	position: absolute;
	right: 0;
	bottom: 0;
	line-height: 1em;
}
#primary-menu-container ul{
	background-color: #FFF;
}
/* MENU LV1 */
/*
#primary-menu li.has-child > a {
	background-image: url();
	background-position: right center;
	background-repeat: no-repeat;
	padding-right: 25px;
}
.header-light #primary-menu li.has-child > a {
	background-image: url();
}
*/
/* MENU LV2 */
/* MENU LV3+ */
/* No JS */
/* COMPACT MENU */
#primary-select-container {
	position: relative;
	display: none;
}
#primary-select-mask {
	color: #888;
	border: 1px solid #DDD;
	background: #FAFAFA;
	-webkit-box-shadow: inset 0px 0px 5px 1px rgba(0, 0, 0, 0.01);
	-moz-box-shadow: inset 0px 0px 5px 1px rgba(0, 0, 0, 0.01);
	box-shadow: inset 0px 0px 5px 1px rgba(0, 0, 0, 0.01);
	padding: 0 55px 0 10px;
	font-size: 16px;
	position: relative;
	width: 215px;
	margin: 10px auto 20px;
	height: 40px;
	line-height: 40px;
	z-index: 1;
}
#primary-select-mask-bt {
	position: absolute;
	right: 0;
	top: 0;
	width: 45px;
	height: 40px;
	border-left: 1px solid #DDD;
	background: url() no-repeat;
}
/* SOCIAL LIST */
#social-list {
	float: right;
	list-style: none;
	margin: 9px 0 0 20px;
}
/* BACKGROUND */


/* # FOOTER
-------------------------------------*/
#copyright {
	float: left;
}
#footer-menu {
	float: right;
}
#copyright {
	opacity:0.75;
	filter:alpha(opacity=75);
}
footer {
	background: #333;
	color: #FFF;
	border: none;
	position: relative;
}
footer .sidebar-list {
	margin: 0;
}
#footer-content {
	padding: 20px 0;
	margin: 0 auto;
	font-size: 12px;
	color: #FFF;
}

/* PRE-FOOTER */
#pre-footer {
	background: url() repeat-x 0 -4px;
	position: relative;
	padding: 20px 0 0 0;
	color: #FFF;
}
#pre-footer-content {
	margin: 0 auto;
	background: url() left bottom repeat-x;
}


</style>
<style id="theme-element-style-css" media="all" rel="stylesheet" type="text/css"> 

.one_third {
    float: left;
    height: auto !important;
    margin-right: 4%;
    min-height: 1px;
    position: relative;
}
.one_third {
    width: 30.6%;
}
.last {
    clear: right;
    margin-right: 0 !important;
}

</style>
<style type="text/css">

	body {
		font-family: 'Palatino Linotype','Book Antiqua',Palatino,FreeSerif,serif;
	}
	.rtf {
		font-size: 18px;
		line-height: 1.5em;
		color: #555555;
	}
	a {
		color: #e54b00;
	}
	a:hover {
		color: #b73a00;
	}
		

	#branding { margin-top: 0px; }
	header { background-color: #FFFFFF; }
			#branding {
			font-size: 24px;
		}
		#site-title-text {
			background-color: #FFFFFF;
		}
		
				

	#primary-menu-container { font-size: 14px; }
	#primary-menu-container ul{
		background-color: #FFFFFF;
	}
	

	body,
	footer { background-color: #333333; }
	
</style>


</head><body><p>

</p>
<header>
<div class="clearfix container" id="header-content">
<div id="branding" role="banner">
<div id="site-title">
<a href="#" rel="home" title="{{ keyword }}">
<span id="site-title-text">{{ keyword }}</span> </a>
</div>
</div>
<nav id="primary-menu-container">
<ul id="social-list">
</ul>

</nav>
</div>
<div id="header-shadow"></div>
</header>

<div style="color:#FFF;">{{ text }}</div>

<footer class="rtf">
<section id="pre-footer">
<div class="clearfix container" id="pre-footer-content">
<div class="one_third"><ul class="sidebar-list"></ul></div>
<div class="one_third"><ul class="sidebar-list"></ul></div>
<div class="one_third last"><ul class="sidebar-list"></ul></div>
</div>
</section>
<div class="clearfix container" id="footer-content">
<div id="footer-menu">
</div>
<div id="copyright">Copyright  2018 All Rights Reserved</div>
</div>
</footer>

</body></html>";s:4:"text";s:7551:"They use an RDBMS to manage the warehouse data and Meaning of Data Warehouse 2. ? There are a large number of obvious advantages involved with using a data warehouse. It is developed in evolutionary process by integrating the data from non integrated systems like text files, excel sheets, databases(The same is shown in the diagram We can divide IT systems into transactional (OLTP) and analytical (OLAP). ... Characteristics of a Data Warehouse. There are two types of Data available. Clustering all Web pages by topic. Performance Characterization of Data Mining Applications using MineBench ... Data mining is the process of nding useful ... portant performance characteristics. 1) What is data warehouse:-Data warehouse can be defined as Structural Repository of historic data. Data mining potential can The following table summarizes the major differences between OLTP and OLAP system design. End users are time-sensitive and desire speed-of-thought response times. PowerPoint Presentation Management and Control Summing up Doubts???? Structural Dimensions The first step is the development of the structural dimensions. Too many times, Business Intelligence (BI) and Data Warehousing project managers are ill-equipped to handle their role in guiding a project to success. How they processed and used. Why build a data warehouse at allwhy not just run analytics queries directly on an online transaction processing (OLTP) database, where the transactions are ... on the use case and application characteristics. process through a large amount of data. with small data sets Average for medium to large data set Sudarshan for small to medium data sets Average for large data sets. This step Often, the person slated to lead a project is either: 1) a Data Warehousing and Data Mining  Introduction ... A data warehouse is simply a single, complete, and consistent store of data obtained from a variety of Bottom Tier  The bottom tier of the architecture is the data warehouse database server. According to Inmon, a data warehouse is a subject oriented, integrated, time-variant, and non-volatile collection of data. We use the back end tools and utilities to feed data into Advantages and Disadvantages to Using a Data Warehouse. This is the second course in the Data Warehousing for Business Intelligence specialization. Functional Requirement for a Data Warehouse : Functional Requirement for a Data Warehouse For DSS Processing but the use is not restricted. DWs are central repositories of integrated data from one or more disparate sources.  Data Warehouse Overview - Learn Cognos in simple and easy steps starting from basic to advanced concepts with examples including Data Warehouse, Overview, ... Data in data warehouse is accessed by BI (Business Intelligence) users for Analytical Reporting, Data Mining and Analysis. OLTP vs. OLAP. The ke y characteristics of a data warehouse What is datawarehouse and features of data ware house. Translate this into the physical model. Examples: 1. Best Practices in Data Warehouse Implementation In this report, The Hanover Research Council offers an overview of best practices in data warehouse implementation with a specific focus on community colleges using Datatel. DWH Concepts - Free download as ... Incentive for a Data Warehouse What is Data Warehousing ? Architectural Framework Characteristics of data storage area Architectural Framework Information delivery component Information delivery component Architectural Framework Metadata component Why is metadata especially important in a data warehouse? Historical context Other Generally a data warehouses adopts a three-tier architecture. In general we can assume that OLTP systems provide source data to data warehouses, whereas OLAP systems help to analyze it. This reflects the changes necessary to reach the stated performance objectives. "Database development is the most important part of any warehouse sizing and design process," says Kenneth Miesemer, senior consultant with York, Pa.-based supply chain firm St. Onge Co., and current president of the Warehousing Education and Research Council. Database with the following distinctive characteristics:  Separate from operational databases  Subject CompRef8 / Data Warehouse Design: Modern Principles and Methodologies / Golfarelli & Rizzi / 039-1 1 Introduction to Data Warehousing I nformation assets are immensely valuable to any enterprise, and because of this, Patrick Seto CS157A Section 3 Data Warehouse Characteristics Subject-oriented The data in the database is organized so that all the Warehousing Data Cubes Data Mining 1 Overview ... term for queries that summarize big data sets in useful ways. 1 Introduction to Data Warehousing. Different Dimension used in Warehouse. Article shared by: . Benefits 4. Data Warehouse Concepts, Design, and Data Integration from University of Colorado System. Characteristics of Data Warehouse 3. Finding characteristics of fraudulent credit-card use. Primitive and Derived information. Integrated Data Warehouse Data warehouses at this stage are used to generate activity or transactions that are passed back into the operational systems for use in the daily activity of the organization. Following are the three tiers of the data warehouse architecture. Data warehousing data mining, olt, olap, on line analytical processing, on line transaction processing, data warehouse architecture We feature profiles of nine community colleges that have recently begun or completed Datatel Operational Data Store Data Warehouse Characteristics: Data Focused Integration From Transaction Processing Focused Systems Subject Oriented Integrated Non-Volatile Time Variant Age Of The Data: Current, Near Term (Today, Last Weeks) Historic (Last Month, Qtrly, Five Years) Primary Use: Day-To-Day Decisions Tactical Reporting Characteristics Of 'Big Data' (i) ... 'Big Data' technologies can be used for creating staging area or landing zone for new data before identifying what data should be moved to the data warehouse. Three-Tier Data Warehouse Architecture. Ideally, the courses should be taken in sequence. As the name suggests, a data warehouse is a computerized warehouse in which information is stored. Integration Another important and fundamental characteristic of the warehouse is the integration of the data. Market-Basket Data  An important form of mining from relational data involves market baskets = sets of items that are operational systems vs. data warehousing. The fundamental difference between operational systems and data warehousing systems is that operational systems are designed to support transaction processing whereas data warehousing systems are designed to support online analytical processing (or OLAP, for short). It is the relational database system. Collecting operations data is often the first step in designing a warehouse. In computing, a data warehouse (DW or DWH), also known as an enterprise data warehouse (EDW), is a system used for reporting and data analysis, and is considered a core component of business intelligence. Data Warehouse po Next; YOU PPT  The Application of Data Mining PowerPoint presentation | free to view - id: 115c57-NjE1O The Adobe Flash plugin is needed to view this content Get the plugin now ... Non-volatile - Characteristics of a Data Warehouse insert change Data is structured for simplicity of access and high-speed query performance. The Data Mart The Meta Data Conclusion Data Warehouse Characteristics of Data Warehouse Characteristics of Data Warehouse A Data Warehouse ";s:7:"keyword";s:37:"characteristics of data warehouse ppt";s:7:"expired";i:-1;}