The Implementation of Flight Operational Quality Assurance (FOQA) and Research Paper - 1

The Implementation of Flight Operational Quality Assurance (FOQA) and Flight Data Monitoring (FDM) plans and the Challenge of Effective Integration - Research Paper Example It is for this reason that such bodies as the International Civil Aviation Authority (ICAO) continue to enforce international policies that seek to minimise the number of air travel incidences and accidents. In its 2014 safety report, the ICAO recorded decrease in the number of accidents per one million departure from 3.2 in 2012 to 2.8 in 2013 (ICAO, 2014). This was against 2011 and 2010 rates of 4.2 each. This statistics shows that a lot of progress is being achieved in aviation safety. This research paper therefore seeks to investigate ways in which the implementation of two major flight safety systems namely the flight operational quality assurance (FOQA) and flight data monitoring (FDM) can aid in improving the safety status in air travel. This is done along the need to understanding the challenges that come with the effective integration of these and other flight safety systems. The FOQA and FDM systems are often thought of as being the same type of system and representing the same outcome. Klein and Militello (2011) however explained that even though these two may be very similar and used interchangeably, they are not the same and do not represent the same outcome. FDM can be said to be the parent safety system introduced by the Flight Safety Foundation and approved by the ICAO for practice for processing recorded data from routine flights. The overall aim of such processing of recorded data is to ensure that there is effective operational risk assessment for all aircrafts that are over 27 tonnes (Diehl, 2013). Out of the FDM, the FOQA was born very specifically by the US Federal Aviation Authority (FAA) which exempted itself from the ICAO’s mandatory requirement on January 1, 2005 for National Aviation Authorities (NAA) through the FDM (UK Health and Safety Executive, 2011). As a flight safety system, the FOQA acts as a voluntary program or guideli ne for capturing, analysing and visualising all forms

Data warehouse, data mart and business intelligence Essay - 1

Data warehouse, data mart and business intelligence - Essay Example ique data structure that allows comparatively rapid and trouble-free performance of big and complex queries over large amounts of data (Business Intelligence Secrets, 2012). Additionally, the data warehouse is built to support the business intelligence tasks and decision support systems of an organization. However, the data warehouse is developed on the basis of relational database that supports queries and reporting instead of traditional business transaction processing. Moreover, it typically holds historical data resulting from transaction data; as well it can gather data from other corporate sources. Also, it divides bossiness analysis workload from corporate operations workload and allows a business to merge data from numerous sources (Oracle Corporation, 2002; Einbinder, Scully, Pates, Schubart, & Reynolds, 2001). There is another concept related to business intelligence known as data mart, it is a business decision support structure that integrates data from different sources and focuses on major processes or tasks of the business. In addition, the data marts encompass exact business related processes and principles like that forecasting sales, determining performance and influence of marketing promotions, assessing the influence of new product launching on business income or calculating and forecasting the working of a new business division or department. In fact, data marts are strictly business related software systems. Though, data marts can capture large amounts of data, even hundreds of gigabytes, but it cannot be larger than the data warehouse, which is also used by similar businesses. On the other hand, data marts are more aligned with specific company motives, system requirements and planning and analysis are performed in an effective manner and as a result implementation, design, i nstallation and testing are less expensive as compared to data warehouses (Demarest, 1993; Firestone, 1997). In addition, they can be developed rapidly and they are