Data Management

Discussion 1:

Risks of poor Data Quality for the business:

The data that is gathered will be helpful for building various technologies within the organization so that the problems will be warehouse will be exposed in clear manner and the raw materials define the quality of the data. The data in the association will be helpful for building different advances with the goal that it will have the capacity to uncover the issues that identified with distribution centre data. The nature of the data will totally relies upon the nature of the crude materials that assembled by the association for making valuable materials. Poor data quality will stop to play out the exchanges of the business (forbes.com, 2017).

There are unfavorable effects on the association because of low quality of data. As the business procedures will for the most part relies on the data, low quality of the data will prompt wasteful aspects. Because of wasteful aspects, the work should be done again with the goal that it prompts results for different costs. Poor choices will be made by the association on account of poor data quality. The basic choices that made because of poor data quality will have the capacity to prompt intense outcomes in the association. Question will be made by the low quality of the data (forbes.com, 2017).

Data mining:

The procedure that is utilized for extraction the data which is in usable from the bigger arrangements of the data that is displayed as crude data will be treated as Data mining. At least one programming will be utilized by the data mining apparatuses so as to break down the data designs. Data mining can be utilized in different applications, for example, science and just as research. With the assistance of data mining procedures, the association will have the capacity to grow more methodologies which are identified with different elements of the business. The business will turn out to be nearer to targets with the goal that the association will have the capacity to take better choices (sas.com, 2019).

Text mining:

By and large data will be accessible as computerized signals. The procedure in which is nontrivial in which extraction of the concealed data from beforehand obscure and helpful data which has capability of data as text can be considered as text mining. Text mining devices will be considered as like the text mining in numerous angles. The text mining procedure will have the capacity to manage the capacities and activities with the goal that the data about the genuine sentiments so the data will be removed. The extraction of the information will be gathered from the information that has been hidden. The data mining and as well as text mining will have the close relation (linguamatics.com, 2019).   

References

forbes.com. (2017). Poor-Quality Data Imposes Costs and Risks on Businesses, Says New Forbes Insights Report. Retrieved from,https://www.forbes.com/sites/forbespr/2017/05/31/poor-quality-data-imposes-costs-and-risks-on-businesses-says-new-forbes-insights-report/

linguamatics.com. (2019). What is NLP Text Mining? Retrieved from,https://www.linguamatics.com/what-is-text-mining-nlp-machine-learning

sas.com. (2019). Data Mining: What it is and why it Matters. Retrieved from,https://www.sas.com/en_in/insights/analytics/data-mining.html

Discussion 2:

What are the business costs or risks of poof data quality? Support your discussion with at least 3 references.

Data is the bloodstream of every organization so having data with poor quality could have a devastating effect on an organization decision.  Anders et al. (2011) describe three types of data that organizations use for decision making. They consist of master data, transactional data, and historical data. Master data is described as data that is gotten from business activities such as customers, product or employees data. Transactions data is data from transactions such as invoices, orders, payment information while historical data has to do with data from past events. In all types, having poor quality data can affect the different aspect of the decision-making process. Some of this negative impact include

·      Poor customer satisfaction

·      Poor economic performance of an organization

·      Higher operational cost

·      Poor use of resources

·      Increased waste of time

 

 What is data mining? Support your discussion with at least 3 references.

Witten et al (2011) define data mining as the process of finding patterns in data. This is done automatically to avoid the tedious tasks of digging through data manually. This is used for databases and the goal is to analyze data that can be used for decision making or problem-solving. Data keeps multiplying at an extremely fast rate, data mining is necessary to look through the data automatically and find what is relevant in the data in order to use it for informed decisions.

3.        What is text mining? Support your discussion with at least 3 references

Text mining also known as text analytics is the use of technologies to examine a large number of texts from documents in order to transform it from unstructured data to structure data for analysis. This requires the use of artificial intelligence for processes. Text mining is different from the traditional keyword search where it only brings back documents that have only the keywords specified. In text mining, the documents are read by the artificial intelligence and it can identify facts and relationships.

 

Anders, H., Frederik, Z., & Dennis van, L. (2011). The costs of poor data quality. Journal Of Industrial Engineering And Management, Vol 4, Iss 2, Pp 168-193 (2011), (2), 168. doi:10.3926/jiem..v4n2.p168-193 

Witten, I. H., & Hall, M. A. (2011). Data Mining: Practical Machine Learning Tools and Techniques. Burlington, MA: Morgan Kaufmann.

What is NLP Text Mining? (2018, July 24). Retrieved from https://www.linguamatics.com/what-is-text-mining-nlp-machine-learning