Demonstrate the data gap analysis

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Reference no: EM133360960

Assignment:

Data gap analysis can be referred to as the process of inspecting an existing or planned big data infrastructure with the aim of identifying issues, risks and inefficiencies associated with the use of data in an organisation's operations. Such analysis requires an integrated view of organisational data's technical, managerial and legal aspects. This activity represents a key initial step towards the implementation of data-driven business decision-making. you must demonstrate the data gap analysis for a case study of your choice.

Case study

A significant project the data science team is working on is GrabShare, Grab's commercial service that enables passengers to carpool with another passenger heading in the same direction. "To get passengers quickly to their destinations, GrabShare pairs just two passenger bookings with similar trip routes within a single trip," says Lye. Passengers will experience a maximum of two stops before reaching their destinations. GrabShare focuses on maximizing drivers' potential earnings by reducing the time and distance spent on a single GrabShare ride, allowing drivers to complete more jobs per hour to boost their income and reduce fuel consumption. Two key metrics are involved in doing this:

1. Match rate - This measures how well they match the first passenger with another passenger going in the same direction.

2. Match quality - This measures the trade-off in time a passenger faces by choosing to share a ride with someone else. The key is to strike a balance between match rate and match quality, while aiming for higher efficiency in putting more people in fewer cars. "With this, it's important to understand how passenger behavior differs from one market to another," says Lye. "For example, GrabShare riders in Singapore are less willing to wait for a ride than GrabShare riders in Indonesia."

Task 1

Perform data gap analysis for an organisation or project of your choice. Your response should include

? Brief background to the organisation or project in question.

? Identification of the key data sources and datasets available to the organisation.

? Inspection of data integrity and current or potential gaps in data analytics and data protection.

Task 2

Using the findings of Task 1.1 recommend improvements to the organisational data analytics processes. These should be centred around the following:

• Reorganisation of the current data-driven processes to streamline and enhance the data analytics and decision-making.

• Roadmap to the development or enhancement of the big data infrastructure.

• Compliance aspects of the proposed changes in data analytics.

Task 3

Explain how the proposed big data analytics can be used in organisational decision-making. This includes the following:

• Identification of a range of business decisions that can be supported by the enhancements in data analytics proposed in Task 1.2.

• Formulation of a single decision of your choice out of those identified, in terms of the related business question to be solved, involved stakeholders and data available for its support.

Reference no: EM133360960

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