Data visualization: the power to produce an engaging, insightful experience
Visualizing big data
Big data has brought new challenges in visualizing enterprise data of the large volume and rapidly changing contents of Hadoop (hadoop.apache.org) and other big data repositories. Tableau is well known for its interactive exploration capabilities, and because it can connect to a wide variety of databases, it has become popular for accessing and visualizing data. “Many organizations use Tableau as a visual analytics platform to explore their data,” says Ellie Fields, senior director of product development at Tableau. “Businesses have data coming in from multiple sources, and Tableau makes analysis easy enough for everyone to make data-driven decisions.”
The degree to which visualizations have moved beyond pie charts is illustrated by the examples in the Gallery on Tableau’s community website. One set of graphs is designed to illustrate the volatility of cryptocurrencies such as Bitcoin, Dash and Decred. The Y-axis represents the percent by which the currency varied each day, and the X-axis represents the price of the currency. By hovering over a dot, which represents a given percent fluctuation and price, the user can see the high, low and close price for that day and the percent change from the previous day. From just a glance at that scatter chart, it is possible to get a sense of volatility and overall price range for each cryptocurrency.
Tableau’s Viz in Tooltips is an interactive feature that lets users selectively obtain additional information from dashboards. When the user hovers the mouse cursor over a point on a dashboard visualization, a more detailed chart appears, says Fields, “showing data that is automatically expanded to provide more detail about the point on the graph that the user selected.” That option allows the user to view underlying data. “Viz in Tooltip eliminates data clutter by allowing users to view a summary while still being in the context of the dashboard,” Fields says. “This saves space and provides a clean design while encouraging exploration from viewers.”
Visualization plays a vital role in creating meaningful analyses from organizational data. Machine learning and natural language processing will play a key part in delivering insights to more users. The ability to augment data preparation steps, generate insights using natural language interaction and explain the results will be important. The technologies will work in tandem with visualization tools to present insights quickly and clearly, allowing users to understand the data, choose actions that support the organization’s goals and measure the impact of the actions.