Data science news

CRM Software: Does Visualization Matter?

CRM software has evolved from simple contact management solutions to sophisticated commercial databases, branching out to marketing, customer support, accounting and more.

What is bizarre is that the user interfaces of these solutions have remained stuck in the 1990s: tables, pie charts, report builders are commonplace, as are simple views on the central database whose only value is the raw information they contain.

We believe these negative consequences of poor data visualization can be avoided. In the context of CRM solutions, visualizations can be leveraged in three areas.

Mental models
Visual alerts.
Playability

When everyone sees the same data the same way – Visualization Week on Successful Workplace

Visualization is an extremely powerful tool for data scientists and business users and the marketplace has been very kind to the products that make visualization possible. It was only a few years ago that we believed that the best we could do was teach our brains to see data like a computer (think: The Matrix).

Tom Davenport, writing in Harvard Business Review, made the following statement on the importance of visualization:

“Those of us who believe that managers make better decisions when key data are presented visually tend to get very excited about all the innovation going on in the graphical display of information. However, if you work in a large organization and want it to make better use of data visualization, I’d argue that commonality is more important than creativity. If you can establish a common visual language for data, you can radically upgrade the use of the data to drive decision-making and action.”

Four Things You Need To Know In The Big Data Era

Big Data has been declared the “sexiest job of the 21st century” and it’s already reshaping corporate decisionmaking and even talent recruitment. As Phil Simon, author of Too Big to Ignore: The Business Case for Big Data, points out, “In a recent report, McKinsey estimated that the U.S. will soon face a shortage of approximately 175,000 data scientists.” Seemingly everyone wants in on Big Data, a blanket term for the massive amounts of information we generate today. (Simon notes that roughly 80 percent of that information is unstructured  – such as tweets, blog posts, Facebook likes, or YouTube videos – as compared to the smaller and easier-to-manage “structured data” that populates spreadsheets.) With the impending rise of wearable technology and “The Internet of Things,” it appears the pace of data creation will only increase. Here are four things you need to know about the Era of Big Data.

  • It’s Not Just for Large Companies
  • Data Visualization may be the Next Big Thing
  • Intuition isn’t Dead
  • It Isn’t a Panacea.

5 Ways Big Data Analytics Caught J.K. Rowling in the Act : Pseudonyms Can’t Hide

By now you surely know that the Robert Galbraith, the first-time author of a new crime novel called The Cuckoo’s Calling, is not a Robert, or a first-time author. Robert Galbraith is none-other than J.K. Rowling, the superstar author of the Harry Potter series. Unraveled by the UK’s Sunday Times, Richard Brooks, the paper’s arts editor, received an anonymous tweet claiming Robert Galbraith was in truth J.K. Rowling.

Lo and behold, Big Data analytics cracked Rowling’s coded secret. Mr. Brooks enlisted the help of two forensic linguistic computer scientists to see if there were any similarities between “The Cuckoo’s Calling,” “The Casual Vacancy” and the last Harry Potter novel, “Harry Potter and the Deathly Hallows.” This is when the story gets about as juicy as juicy gets for a geek.

5 ways Big Data can get you caught up

    • Comparing all of the word pairings, or sets of adjacent words, in each book.
    • Tests that searched for “character n-grams”, or sequences of adjacent characters.
    • Tallied the 100 most common words in each book and compared the small differences in frequency.
    • Testing completely separates a word from its meaning, by sorting words simply by their length.
    • Principal Component Analysis: compare all of the books on six features: word length, sentence length, paragraph length, letter frequency, punctuation frequency, and word usage.

In 5 hours, computer scientists were able to utilize forensic linguistics on Big Data and prove well enough to put their word behind it that Robert Galbraith was none-other than J.K. Rowling.

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