Question 1 - Week 1 (Thursday): Based on the Ledford article‚ what special issues must be considered for corporate data which is not fully digitized? What are the potential risks associated with the loss of this type of data? Suchlike as vital as their electronic counterparts‚ are hardcopy files‚ records‚ and data. It can thus far be disputed that the softcopy of records and data is per se attributable to their lack of ability for retrieval in such instance of breakdown‚ stealing‚ or natural
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2 Areas of data processing 1. Business Data processing (BDP) . Business data processing is characterized by the need to establish‚ retain‚ and process files of data for producing useful information. Generally‚ it involves a large volume of input data‚ limited arithmetical operations‚ and a relatively large volume of output. For example‚ a large retail store must maintain a record for each customer who purchases on account‚ update the balance owned on each account‚ and a periodically present a
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240 - INTRODUCTION TO DATA PROCESSING/MANGEMENT OF INFORMATION TECHNOLOGY Objectives To give a thorough and up-to-date grounding in the realities of commercial applications of Information and Communication Technologies (ICT’s). To Examine the roles of data‚ information and knowledge within modern business organisations‚ and the roles that information and communication technologies (ICT’s) play in supporting people and groups within organisations. To provide students with a thorough understanding
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Increase Your Data Center Energy Efficiency • Increase Your Data Center Energy Efficiency • Increase Your Data Center Energy Efficiency • Increase Your Data Center Energy Efficiency • Increase Key Best Practices Optimize the Central Plant Quick Start Guide to Increase Data Center Energy How To Start A Problem That You Can Fix Data Center energy efficiency is derived from addressing BOTH your hardware equipment AND your infrastructure. Commit to Improved Design and Operations
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best alternative in the following: Q.1 In the relational modes‚ cardinality is termed as: (A) Number of tuples. (B) Number of attributes. (C) Number of tables. (D) Number of constraints. Ans: A Q.2 Relational calculus is a (A) Procedural language. (C) Data definition language. Ans: B Q.3 The view of total database content is (A) Conceptual view. (C) External view. Ans: A Q.4 Cartesian product in relational algebra is (A) a Unary operator. (B) a Binary operator. (C) a Ternary operator. (D) not defined
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Management in Business-Time value of money-Risk and Return- Risk diversification. Module II Long-term investment decisions – Capital budgeting‚ Different techniques –Traditional and modern methods (DCF method) – Capital Rationing – Risk Analysis in Capital budgeting – An overview of Cost of Capital. Module III Financing decisions – Operating‚ Financial and combined leverage – Capital Structure – Meaning and importance- Theories of capital structure – Net income‚ Net operating income
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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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Q) What are Secondary Data? Secondary Data Secondary data is information gathered for purposes other than the completion of a research project. Data previously collected by someone else‚ possibly for some other purpose that can be used later for making decisions if found suitable for the purpose‚ other than the original one. Secondary data can be acquired from the internal records of the organization‚ their departments‚ subsidiaries or sister organizations and also from external sources‚ such
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s= = x-x2n-1 | Q1n+14‚ Q7+14=84=2postion Q3=3(n+1)4=3(7+1)4=244=6‚ IQR Q3-Q1‚ | CV=sx×1003.297×100%=47%/ n = 5 has a mean of 10.2.four data: 9‚ 10‚ 8 17‚ find the missing data value.x=i=1nxin=8+9+10+17+?5=*5=10.2‚ 5×10.2=51 Therefore: 8+9+10+17+?=51Therefore: 8+9+10+17+?=51Simplifying: 44+?=51And so ?=51-44=7Thus the missing data value is 7. | Variance/s2= x-x2n-1‚ [3-72+4-72+7-72+7-72+9-72+12-72]6-1 =545 =10.8 | egA manufacturer of insulation randomly selects 20 winter days
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Enhancing Customer Data Enhanced Customer Data Repository is a secure and fully supported data repository with problem determination tools and functions. It updates problem management records (PMR) and maintains full data life cycle management. · combination of all the internal structured business data (CRM‚ ERP‚ POS and all the internal system data) and external unstructured data ( Social media data‚ feedback surveys‚ Audios‚ Videos‚ streaming data‚ Call center data‚ images) · unmanageable volumes
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