Discussion

Johnny48
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Discussion1

1)  Business cost or risk poor of data quality

Data is a major factor in a business enterprise that is usually crucial in making a decision that may have an impact towards business progress in making profits or losses. Data provides a clear profile on the progress of the business and interpretation of the information obtained is crucial for business success. The extent of data quality cannot be ascertained but the effect can be concluded by the final returns of the business (Redman, 1998). Data of poor quality may have a detrimental consequence on business by creating an additional cost on the transaction rework, cost on the implementation of new systems, poor service resulting to a loss in customer and loss in production.

 The effect of data quality on cost:

• Implementing new systems

Data warehouses, consolidation of database migration, and integration of new systems is critical to the quality of data as data errors may result in the unsuccessful implementation of the above concept. Quality of data cap increases the cost and time in the implementation of these systems.

• Transaction rework

The transaction is among the service that a business offers to its customers. The transaction resulting from poor data quality may result in poor design in entry procedures and screening of customers’ orders. According to Haug et al (2011), poor data quality results in the mishandling of shipments and orders from the company to the clients resulting in the goods sold being returned or loss of customers. The goods that are not delivered to the right customers in most cases are returned to the business resulting in increased cost of shipping and meeting orders.

• Decision making

Wang  (2008) states that most of the companies require the report in making decision greatly relying on the data. Data quality has a significant impact towards the quality of the report and direct effect to the decision made. Poor data may give a false impression or increase the time in decision making resulting from data flaws.

2)  Data mining concept

This is a process in which data relation and patterns from large datasets are established by sorting and data analysis. The concept of data mining combines artificial intelligence and statistic tools in establishing data trend (Han et. al., 2011).

3)  Text mining

According to Tan (2009), text mining is referred to as a process for acquiring information of high quality from the text. It can also be referred to text analytics or text data mining. Text mining tries to extract the useful information from the normal natural test language. The non-trivial extraction is a system for analyzes of large data with the origin of natural language text. The nature of information handled by text mining is unstructured information there are similarities between text mining and data mining only that tools used in data mining are planned to solve the well-structured data. Traditional text mining a list of standard entities is identified. In identifying data entities it is a requirement that the use of technology which mimics human capacity in disambiguating, understanding and reading the text

Discussion2

For over the past years, I and my colleagues have been working on coming up with a unified system of agency by the name TiD Multi Agency Investments Limited (Angel, 2010). With this we integrated agency services in such a manner that they can be provided by one person. For example one can be an agent of several banks, learning institutions, mobile operators, and government offices by using our software that integrates all the clients.

The project is run by a team of 32 staff members. The breakdown involves3 executive members, 2 project managers and a team of 25 support staff. We have given 4 slots for other interested parties and stakeholders.

The project was set out after identifying the need to set up such an enterprise and its business value. As an organization we had to work against many risks but we saw our goals stronger than the risks.

After intensive analysis of the milestones of the project, return on investments and resources required, the project proved satisfactory and worth our sweat

A good managing team from the brilliant executive together with proper alignment has been our pride, now order the robust growth.

The project has been tested constant changes are updated regularly to ensure its adaptability in the future.

Digital project manager gives the tools for good PPM which we have closely alluded to in our course of events.

 The project aims to target 100000 agency outlets in the world in the first phase. Once the software sales pick root, the number is expected to raise. The project has a potential to rich out 300000 interested clients for purchase of the software globally.

Lone of the challenges we face is that potential clients may lack the financial ability to adapt our software and system guidelines. With this we have set up a team to carry out intense marketing plus education and creating awareness of existence of the project.

The project was a commercial success. However we lacked a central coordinating software or system. This led to slot of lag time when trying to link up individual work. If the projected were to be redone, I would be in for creating a communication hub to ensure easy flow of information within the organization.