The value of useful information in the world of decision-making cannot be over emphasized. This "useful" information is often times buried in huge sized unstructured texts and like gold, needs to be mined. The use of text analysis is growing rapidly as organizations continue to realize how much useful information mined from unstructured data can impact the quality of decisions made. As data continues to grow exponentially, it becomes more challenging for individuals and organizations to make sense of such huge data and so it is only logical for the need for text analysis to also increase in order to meet the need for useful information across industries. This study aims at finding ways of extracting data(structured and unstructured) from web pages, converting the data to text corpus and applying statistical method like time series analysis and cluster analysis to uncover pattern and trends lurking in the text.