Summary of topics

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

The value of data is increasing every day and companies are investing in technologies to enhance the data quality to make business decisions, reduce operational costs and drive their business. There is so much potential in data and analytical capabilities to identify key performance metrics to strategize both tech and business development. Data in its raw state is not useful unless it is enriched and processed for better data quality. Good data quality helps in accurate decision making and enables productivity due to less error prone data. Poor data quality can cost a lot to companies in terms of damage ranging from reputational damage to the loss of revenue. Poor data in financial sector can cause huge fraudulent activities reported and can incur losses. Companies may miss out on opportunities if data is not analyzed to its fullest potential and can lead to fall in sales. Poor and inaccurate data can lead to poor business strategies (Indurkhya, 2015).

What is data mining?

Data mining can be defined as a process to identify anomalies, dig data to discover hidden patterns and connect datasets to predict future patterns and opportunities. The term data mining was coined in the 90’s and allows application of statistics, AI and machine learning to make informed decisions. Data mining can be used to detect fraud, cyber threats and predict future outcomes, exploring market potential and opportunities thereby increasing productivity and revenue (Haug, Zachariassen & Liempd, 2011).

What is text mining? 

It is the process where one can explore and deep dive on large amounts if text data with the use of tools and techniques to identify patterns, hidden trends, keywords and other parts of the data. Mining data cab prove to be useful for identifying potential and valuable insights in business documents, emails, social media posts and even medical evidences. In product management and marketing, text mining plays an effective role in predicting product offerings and customer churn. This helps in improving customer relationship by improving customer experience through customized advertising and help boost sales & increase revenue (Haug, Zachariassen & Liempd, 2011).