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Unit 4 Assessment
Q1. Data integrity refers to data which is consistent, accurate and available when required. Databases help ensure that organisations maintain data integrity by enforcing strict data procedures, . For example, databases which require users to enter specific values in designated fields prevent users from entering data in incorrect fields, such as the case where a user enters a phone number in the date field, or enters data in incorrect ranges and units. Database integrity can also be compromised due to redundant or repeated data. Databases can prevent such threats to data integrity by enforcing entity integrity (to prevent duplicate entries), reference integrity (to ensure that links across data entries are maintained), and domain integrity (to ensure that the appropriate data type is observed throughout the database, and constraining the XXXXX XX XXXXXX to XXXXXXXXXXX ranges). XXXXXXXXXXX, XXXXX checking XXX validation procedures XXX be XXXXXXXXXXX XX ensure that XXX XXXXXXXX XX consistent XXX accurate, which XXXXX to XXXXXXXX XXXX integrity. (Doorn, 2001)
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Doorn, X. H. (XX.). (XXXX).XXXXXXXX XXXXXXXXX: XXXXXXXXXX and Solutions. IGI Global.
XXXXXXX, E., XXXXXXX, L., XXXXXXX, R., Lombardi, X., XXXXXXXX, A., & XXXXXXX, V. (2017). Blockchain-based XXXXXXXX to ensure XXXX integrity in cloud computing XXXXXXXXXXXX.
XX. Data in transactional XXXXXXXXX XXXXXX from those in data warehouses in XXX following XXXX. Foremost, a data warehouse XX a XXXXXXXXXX based XXXXXX, while a XXXXXXXXXXXXX database XX XXXXXXXXXXX based. XXXXXXXX, a transactional XXXXXXXX contains XXXXXXXXXX data, while XXX data in a XXXX XXXXXXXXX is subject XXXXXXX. (XXX, 2000) Thirdly, a transactional database XX normally in XXX form of an online transaction processing XXXXXXXX (XXXX), confined XX a single application and XXXXXX to be analysed, while a XXXX XXXXXXXXX is an XXXXXX XXXXXXXXXX processing (OLAP) database which can be XXXXXXXXX for XXXX XXXXXXXXX. Fourthly, a transactional database is typically XXXXXXX as a XXXXXXXXXX of XXXX to be stored, XXXXXXXX XXX XXXXXXXXX, XXXXX a XXXX XXXXXXXXX has data that XX XXXXX XXXX various sources XXX optimised XXX analytics. Fifthly, a XXXXXXXXXXXXX XXXXXXXX has XXXXXXXXXX data, while XXX XXXX warehouse has XXXXXXXXXXXX XXXX.
Reference
XXX, J., & Kamber, M. (XXXX). XXXX XXXXXX: XXXXXXXX XXX XXXXXXXXXX.
Shin, X. (2003). An exploratory investigation of XXXXXX success XXXXXXX in XXXX warehousing.Journal XX the XXXXXXXXXXX for Information Systems,4(X), 6.
XX. XXXX XXXXXX is relevant to XXXXXXXXXXXXX in the areas XX XXXXXXXX XXXXXXXXX, XXXX XXXXXXXXX, and XXXXXXX XXXXXXXXXXXX, Foremost, data mining, or XXX XXXXXXXX of XXXXXXXX XXXXXXXXX for XXX insights, allows XXXXXXXXX XXX XXXXXXXXXXXXX XX XXXXXXXX XXXXX business XXXXXXXXX. XXX XXXXXXX, a manufacturer XXX use data XX XXXXXX downtimes to XXXXXXX when XXXXX systems XXX XXXXX XX XXXXX XXXX, in order XX XXXXXXXXX XXXXXXXXXX maintenance. (Tan, 2018) Secondly, an XXXXXXXXXXXX XXX XXXXXXXX XXXX mining XX perform XXXX XXXXXXXXX and garner XXX business XXXXXXXX, such XX the XXXXXXXX XX supply and demand XXXXX XX XXXXXXXXXX supply and XXXXXX trends. XXXXXXX, organisations can use data mining for process XXXXXXXXXXXX, XX identifying bottlenecks in XXXXXXXXX XXXXXXX XXXXXXXXXX process data XXX XXXXXXXXXX XXX XXXXXX accordingly in order to XXXXX XX the XXXXXXXXXX and XXXXXXXXXXXX of XXXXX XXXXXXXX XXXXXXXXX.
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XXX, P. N. (2018).Introduction to data mining. Pearson XXXXXXXXX XXXXX.
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XX XXX CIO of a XXXXXXX XXXXXXX XXXXXX XXXXX with an online XXXXXXXX, with department databases in the marketing, customer XXXXXXX, accounts payable, XXXXX XXX XXXXXXXX XXXXXXXXXX XXXXXXXXX, I would apply a business intelligence XXXXXXXXXXXXXX XX XXXXXXX. XXXXXXXX, I would XXXX a data XXXXXXXXX XXXX effectively draws from the disparate transactional XXXXXXXXX from each XX the XXXXXXXXXX XXXXXXXXX. This XXXXX format XXX XXXXX XXX XXXX in a XXXXXX XXXXXXXXX XXX XXXX analytics. I XXXXX then implement an OLAP system, formatted reports, and list reports for XXXX analytics in XXX intermediate business intelligence XXXXXXXXXXXXXX XXXXX, and then implement a dashboard at XXX XXX-XXXX business intelligence infrastructure XXXXX in order to XXXXX XXX ease of user XXXXXX. XXXXXXX, I XXXXX implement integration of XXX business XXXXXXXXXXXX XXXXXXXXXXXXXX XX XXXXX systems, such XX XXX XXXXXXXX XXXXXXXXXXXX management (CRM) XXX XXXXXXXXXX XXXXXXXX planning (ERP) system, so that XXX business intelligence insights can be converted into actionable strategies to be implemented in the XXX XXX XXX XXXXXXX. XXX XXXXXXXX XXXXXXXXXXXX infrastructure should also ensure redundancy XXX scalability, XXX have XXXXXXXXXXXXXX that supports the XXXXXXXXXX of XXXXX XXXX volumes.
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XXXXXXXXXXX, X. X., & Swami, S. N. (XXXX, June). XXXXXXXX XXXXXXXXXXXX XXXXXXX: XXXXXX and XXXXXXXXXXXXXX strategies. InXXXX XXXXXXXXXXXXX XXXXXXXXXX on XXXXXXXXXXX Technology XXXXXXXXXX, XXXX.(XX. XXX-XXX). XXXX.
Olszak, C. X., Ziemba, X., & Koohang, A. (2006). Business intelligence XXXXXXX in the XXXXXXXX infrastructure XXXXXXXXXXX supporting XXXXXXXX-making in XXXXXXXXXXXXX.XXXXXXXXXXXXXXXXX XXXXXXX XX Information, Knowledge & XXXXXXXXXX,X.
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