Text Analytics: A Primer


Text Analytics

Marketing scientist Kevin Gray asks Professor Bing Liu to give us a quick snapshot of text analytics. The interview was first published in GreenBook on January 24, 2017 and on Linkedin on February 9, 2017.

KG: I see “text analytics” and “text mining” used in various ways by marketing researchers and often used interchangeably. What do these terms mean to you?

BL: My understanding is that the two terms mean the same thing. People from academia use the term text mining, especially data mining researchers, while text analytics is mainly used in industry. I seldom see academics use the term text analytics. There is another closely related term, called natural language processing (NLP). Text mining and text analytics usually refer to the application of data mining and machine learning algorithms to text data. NLP covers that and also other more traditional natural language tasks such as machine translation, syntax, semantics, etc. But there is really no clear demarcation between the terms. Read more





Over several decades, numerous studies have been conducted on data visualization practices, including a nice collection of fresh research being conducted in academia and the commercial world today. By data visualization, I mean any visual depiction of data, such as charts and graphs, maps, interactive data experiences and even more esoteric data displays that verge on the territory of art. Read more


5 Keys To Ace Your Analytics Career Transition


achieve-1822503__340So you have heard about the hot new analytics field, the crazy demand for well-trained analysts and the great salary. You’ve decided to throw your hat in the ring. But before you go too far, you must know these 5 key things.

  1. Analytics Aptitude is a must for success. Just because your best friend is an analyst and very happy with his job doesn’t mean you will be too. Make sure you were born to think analytically by testing your analytics aptitude If you score 16 or above in this test, you would likely be happy being an analyst.
  2. Analytics skill development is not optional. It is one thing to have an innate aptitude, it is entirely another to land a job and conduct analytics to drive a business forward. So once you know you have an aptitude, invest in developing hands-on business analytics skills at a bare minimum for any analyst or analytical role. Additionally, having hands-on comfort in predictive analytics skills and A/B testing will come in handy for pure analyst roles. If you are serious about your career transition, I will personally train you when you enroll in our analytics career transition track, which includes the above courses plus real-time experience on a client project.

Read more


How to Tell Stories and Weave a Cohesive Narrative With Data

Rock paintings of Tassili N'Ajjer, Algeria

Rock paintings of Tassili N’Ajjer, Algeria

Evolutionary Advantage of Story

Storytelling is one of the most important evolutionary advantages humans have. That is a bold statement, but I believe it is true.

When ancient man sat around the village fire, telling stories, they were teaching other villagers where to find food, how to successfully capture game, what herbs cured diseases, which animals to avoid (and how!) and other essential survival skills.

This information wasn’t shared in a village newsletter or safety posters on the cave walls (well … I guess they kind of were like early posters … but you know what I mean). Primarily, these lessons came in the form of stories. Read more


Data Driven Trick or Treat – Maximize the “Candy Collection” next time


Another Halloween just got over. I am sure all of you had a great time putting the lights and carving the pumpkin – at least your kids had really a fun time.  I too enjoyed standing at the door and giving out candies. My 11-year-old boy just came after a 2 hour Trick-or-Treat journey in my neighborhood. Not only that he was tired, but he was very upset. I asked him on his concerns and he listed a few: Read more


Story of 5 Blind Men and an Elephant and your Big Data Strategy


Driving value from existing data is one of the most common challenges faced by organizations, however, that doesn’t mean that you should not be working towards a Big Data Strategy. You might think you want to implement a big data strategy but feel you should utilize the data you already have first. This dilemma (or confusion) leads to not having a comprehensive strategy for leveraging your current data (Big, Small, Fast, and Slow) but to plug holes in your current data landscape with the addition of a few new tools and technologies. You have to Read more

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