The most successful data analysts are able to take key data and weave it into a story to convey their point to stakeholders. This is often called a “data story” and is used by analysts who are presenting to an audience who may not understand the intricacies of data. They do this by presenting their findings visually – which is easier for most people to comprehend.  Often time this is through graphs, charts, or other visualization tools like infographics. But is a data story really that important in the world of statistics?

On Monday morning, the tech world got shaken up when Salesforce announced they had acquired data visualization software, Tableau for a whopping $15.7 billion. “We are bringing together the world’s #1 CRM with the #1 analytics platform. Tableau helps people see and understand data, and Salesforce helps people engage and understand customers,” co-CEO of Salesforce Marc Benioff said in a statement after the announcement. What started off as strictly a CRM (Customer Relationship Management) platform, it’s clear that Salesforce is looking to expand their influence to other industries such as data analysis – creating a product that has everything a company needs all in one software.

Tableau’s 11^th Annual Conference concluded another successful conference at the end of October in New Orleans. Attendees got to attend data inspired break-out sessions, Tableau training, as well as networking events. One of the main events was the Iron Viz Championship – a competition between three finalists armed with a dataset and tasked with making the best visualization. Did I mention it was all in front of a live audience? I got to talk to 2018’s Iron Viz Champion, Timothy Vermeiren and asked him more about the championship and why he thinks data visualization is so important.

On October 22^nd, 17,000 data analysts, data scientists, and developers descended on New Orleans for good music, delicious food and Tableau’s 11^th annual conference. For the past 10 years Tableau has put together a data conference that brings together the Big Data community for four days of training, workshops, and networking.