Reference no: EM132415031

Question 1:

Text Analytics, Text Mining, and Sentiment Analysis

1. What is text analytics? How does it differ from text mining?

2. What technologies were used in building Watson (both hardware and software)?

3. Why is the popularity of text mining as an analytics tool increasing?

Note: Your initial post will be your answer to the Question and is to be 300 - 400 words with at least two references. Initial post will be graded on length, content, grammar and use of references. References should always be below each question as they are a different topic and not related in any way.

Question 2:

As large data-sets become more important to both consumer and business publishing, many businesses are experimenting with new ways to visualise data and help it to tell a story. And publishers that get it right - like the New York Times (see above image), Guardian or Wired - win awards, social media kudos and new readers.

But what exactly is involved in the new discipline of data visualisation and what skills do publishers have to nurture, whatever the size of their team? Andy Kirk, of Visualising data, believes that data visualisation is a mixture of art and science, creativity, analysis and project management. He sees 8 "hats" in the data visualisation process, which can either be worn by different members of a team, or can be deliberate mindsets adopted by a solo professional. Understanding how each contributes to the finished product is perhaps the key to creating great data visualisation designs...

Think about the role you played in creating a presentation or working on a project using data visualizations. Choose two of the 8 hats and explain your roles (in relation to these hats) in creating the presentation or finishing the project.

Note: At least 250 words (not including direct quotes). References should always be below each question as they are different topic and not related in any way.