General Electric (GE) is an American multinational conglomerate incorporated in New York and headquartered in Boston, Massachusetts. As of 2016, the company operates through the following segments: aviation, current, digital, energy connections, global research, healthcare, lighting, oil and gas, power, renewable energy, transportation, and capital which cater to the needs of financial services, medical devices, life sciences, pharmaceutical, automotive, software development and engineering industries.
In 2017, GE ranked among the Fortune 500 as the thirteenth-largest firm in the U.S. by gross revenue. In 2011, GE ranked as the 14th most profitable. As of 2012, the company was listed the fourth-largest in the world among the Forbes Global 2000, further metrics being taken into account.
The main purpose of this project is to provide a tool for Quality Assurance of GE to detect any suspicious behaviors flagged by the internal system. The business intelligence tools used here are Tableau and R Shiny, which are helpful for analyst to analyze the structured data and deliver an engaging dashboard for audience. For the overview dashboard, 4 business questions will be addressed accordingly through the filters on the left panel. Following on from that, any further investigation for each graph will be examined through the specific dashboard. This dashboard will help audience to break down the dilemma into smaller parts by using top-down approach, starting with Business, then GUID and finish with description of violation.
In order to tackle some of the challenges GE may confront when detecting fraud and unusual activities, some business questions have been raised. There will be 5 questions in total classified into 2 categories which are spatial and time series analysis.
Time series analysis:
- Number of records by months of years.
- Number of records by days of months.
- Number of records by days in a year.
Spatial analysis?
- Number of records by country.
- Number of records in United States.
Those business questions will enable firm owners or board of directors to make a wise decision on Quality Assurance by performing a comprehensive regular check on specific months or days in the month as there is a high possibility of occurrences in the past. For the spatial analysis, the authority can have an overview of the heat distribution all over the world and in each state of US explicitly. Those graphs can be extremely helpful to prevent the fraud worldwide especially when GE functions in global world. Likewise, the questions about the pattern in the department allows GE to concentrate on the department with unusual activities.