Graphical Representation of Data Chapter 3 ☞ (Paste Examples of any graphs‚ diagrams and maps showing different types of data. For example‚ relief map‚ climatic map‚ distribution of soils maps‚ population map) REPRESENTATION OF DATA Besides the tabular form‚ the data may also be presented in some graphic or diagrammatic form. “The transformation of data through visual methods like graphs‚ diagrams‚ maps and charts is called representation of data.” The need of representing data graphically: Graphics
Premium Cartography Map
Paper Creating a Data Warehouse Introduction Data warehouses are the latest buzz in the business world. Not only are they used to store data for reporting and forecasting‚ but they are part of a decision support system. There are many reasons for creating and using a data warehouse. The data warehouse will support the decisions a business needs to make‚ usually on a daily basis. The data warehouse collects data‚ consolidates the data for reporting purposes. Data warehouses are accompanied
Premium Data warehouse
Conceptual Data Models for Database Design Database Design Process The database design process consists of a number of steps listed below. We will focus mainly on step 2‚ the conceptual database design‚ and the models used during this step. Step 1: Requirements Collection and Analysis ▪ Prospective users are interviewed to understand and document data requirements ▪ This step results in a concise set of user requirements‚ which should be detailed and complete. ▪ The functional
Premium Entity-relationship model
Chapter 3 – Data Visualization Chapter 4 – Summary Statistics Data Mining for Business Intelligence Shmueli‚ Patel & Bruce © Galit Shmueli and Peter Bruce 2010 Data Visualization • “A picture is worth a thousand words” • Data visualization and summary statistics help condense data • Effective presentation • Supports data cleaning (identify missing values‚ outliers‚ incorrect values‚ duplicates) and exploring (combine some groups) • Helps identify suitable variables • Mandatory initial step for
Premium Data analysis
4th Generation Data Centers: Containerized Data Centers ITM 576 – Fall 2011 October 26th‚ 2011 Prepared By: Mark Rauchwarter – A20256723 Abstract The 4th generation of data centers is emerging‚ bringing with them a radical redesign from their predecessors. Self-contained containers now allow for modularity and contain the necessary core components that allow this new design to function. This paper discusses the advancements in data center management and the changes in technology and business
Premium Data center Uninterruptible power supply Containerization
65. The quartiles for the class were 30‚ 34 and 42 respectively. Outliers are defined to be any values outside the limits of 1.5(Q3 – Q1) below the lower quartile or above the upper quartile. On graph paper draw a box plot to represent these data‚ indicating clearly any outliers. (7) Jan 2001 2) The random variable X is normally distributed with mean 177.0 and standard deviation 6.4. (a)
Premium Random variable Normal distribution Probability theory
Transforming Logical Data Models into Physical Data Models Susan Dash Ralph Reilly IT610-1404A-01 According to an article written by Tom Haughey the process for transforming a logical data model into a physical data model is: The business authorization to proceed is received. Business requirements are gathered and represented in a logical data model which will completely represent the business data requirements and will be non-redundant. The logical model is then transformed into a first cut physical
Premium Data modeling SQL Database
Rebecca Shockley‚ Michael S. Hopkins and Nina Kruschwitz Big Data‚ Analytics and the Path From Insights to Value REPRINT NUMBER 52205 THE NEW INTELLIGENT ENTERPRISE Some of the best-performing retailers are using analytics not just for finance and operational activities‚ but to boost competitive advantage on everything from displays‚ to marketing‚ customer service and customer experience management. Big Data‚ Analytics and the Path From Insights toValue How the smartest organizations
Premium Data management Business terms Management
In the late 1970s data-flow diagrams (DFDs) were introduced and popularized for structured analysis and design (Gane and Sarson 1979). DFDs show the flow of data from external entities into the system‚ showed how the data moved from one process to another‚ as well as its logical storage. Figure 1 presents an example of a DFD using the Gane and Sarson notation. There are only four symbols: Squares representing external entities‚ which are sources or destinations of data. Rounded rectangles
Premium Data flow diagram
Introduction This report will give an overview of the aim behind collecting data‚ types of data collected‚ methods used and how the collection of the data supports the department’s practices. It will also give a brief outlook on the importance of legislation in recording‚ storing and accessing data. Why Organisations Need to Collect Data * To satisfy legal requirement: every few months there is some request from the government sector to gather‚ maintain and reports lots of information back
Premium Human rights Law Data Protection Act 1998