Summary of topics

What are the business costs or risks of poor data quality? 

Poor data quality can be in different ways, this can be the collection of the data from different sources including their customers and their clients. While collection can be a monumental task to make customers and client believe their integrity in maintaining their data, data can be easily managed and manipulated in their handling processes. Many organizations faced tough challenged to maintain their customers data and proving their integrity for example Equifax which faced a biggest customer data breach in 2017 has become very expensive for the company and they had to face a great administrative challenge. While it is important to collective the data and it should be maintained with highest level of integrity and not misusing their confidential data for their business profits (Harding, 2018).

What is data mining?

It is cleansing of the data to form a structure which can be visualized in the form of grant charts, graphs and bars using different tools like Amazon S3 Data Mining. This is helpful in indenting the patterns of the data and their flow using machine learning, the ultimate goal of Data mining is to extract information using intelligent methods like statistics and operation research. This structural analysis helps the analytics to predicts the future pattern of how data can be changed in terms of consumption. The visualized data is used to make decisions using natural language processing based on the structural patterns identified (Weiss, Sholom, Indurkhya, Nitin, 2019).

What is text mining?

Text mining is utilized by various organizations including administrative associations use this technology for their record management and search for specific document in their digital library. includes data recovery, lexical investigation to contemplate word recurrence conveyances, design acknowledgment, labeling/comment, data extraction, information mining procedures including connection and affiliation examination, perception, and prescient investigation. Text mining application is not limited to any one industry this is mainly used to identify specific text or term in their entire handbooks and their entire written sources includes e-books, web articles (Miner, Elder, Hill, Nisbet, R., Delen & Fast, 2012). Text mining technology involves an input that is consisted of a text or a phase that is phrased and later searched for its matching in their database so to find a match or to identify it as a new addition. The general objective is, basically, to transform text into information for investigation, through use of normal language preparing (NLP), various sorts of calculations and explanatory strategies. Text mining requires a significant period of this cycle for the understanding and to produce analytical search results from the accumulated data.