Primary research is an important strategy practised in this course‚ usually in the second and third assignments. The following methods are typically used: o Survey o Interview o Site observation When conducting any kind of field research‚ Cunningham et al suggests the following steps: 1. Review your notes on the problem to determine what information you need from your primary research. 2. Establish objectives by identifying specific tasks you must complete. 3. Set up schedule for completing
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.......................................................................................... 3 2.1.2 Non-functional requirement ............................................................................................. 5 3. Logical design: Data Modeling (ERD) .................................................................................... 6 4. Logical design: Process Modeling (DFD) ............................................................................... 9 5. Decision
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Reliable Primary Sources Primary sources are original records created at the time or after historical events occurred. Primary sources may include letters‚ manuscripts‚ diaries‚ journals‚ newspapers‚ speeches‚ interviews‚ memoirs‚ photographs‚ audio recordings‚ video recordings‚ research data‚ and objects or artifacts from the time in order for it to be considered reliable. These sources are raw materials that help interpret the past. Not every primary source is completely reliable‚ because they
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Experiment 2 Preparation of Primary Standard solutions and Standardizing Acid and Base solutions Objectives: The objective of this experiment is: 1- To prepare two primary standard solutions‚ KHP and Na2CO3 2- To standardize a sodium hydroxide solution using the prepared primary standard KHP. 3- To standardize a hydrochloric acid solution using the prepared primary standard Na2CO3. 4- To calculate the concentration of an unknown acid or base. Introduction A primary standard is a standard that
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An Oracle White Paper July 2010 Data Masking Best Practices Oracle White Paper—Data Masking Best Practices Executive Overview ........................................................................... 1 Introduction ....................................................................................... 1 The Challenges of Masking Data ....................................................... 2 Implementing Data Masking .............................................................. 2
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Components of DSS (Decision Support System) Data Store – The DSS Database Data Extraction and Filtering End-User Query Tool End User Presentation Tools Operational Stored in Normalized Relational Database Support transactions that represent daily operations (Not Query Friendly) Differences with DSS 3 Main Differences Time Span Granularity Dimensionality Operational DSS Time span Real time Historic Current transaction Short time frame Long time frame Specific Data facts Patterns Granularity Specific
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annual profits to their 1994 value‚ using an 11% cost of capital‚ the project will be worth undertaking (see details in slide 1)‚ assuming the price of aluminum holds at or above this level. Projections of primary world aluminum supply and demand To estimate the supply and demand levels of primary aluminum 5 years from now‚ we analyzed current supply capacity and world consumption. Supply Beginning with future supply‚ we assumed that producers would continue production as long as the market price
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Data Collection: Data collection is the heart of any research. No study is complete without the data collection. This research also includes data collection and was done differently for different type of data. TYPES OF DATA Primary Data: For the purpose of collecting maximum primary data‚ a structured questionnaire was used wherein questions pertaining to the satisfaction level of the customer about pantaloons product(apparel)‚ the quality‚ color‚ variety of products‚ the availability of different
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PRINCIPLES OF DATA QUALITY Arthur D. Chapman1 Although most data gathering disciples treat error as an embarrassing issue to be expunged‚ the error inherent in [spatial] data deserves closer attention and public understanding …because error provides a critical component in judging fitness for use. (Chrisman 1991). Australian Biodiversity Information Services PO Box 7491‚ Toowoomba South‚ Qld‚ Australia email: papers.digit@gbif.org 1 © 2005‚ Global Biodiversity Information Facility Material
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TYPES OF DATA AND COMPONENTS OF DATA STRUCTURES Data types 1. Primitive: is a data type provided by a programming language as a basic building block 2. Composite: is any data type which can be constructed in a program using its programming language’s primitive data types and other composite types 3. Abstract: is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics
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