The rate at which data is being generated in our world today is growing at an astounding rate—think structured data, unstructured text-based content, sensor data, weblogs, social data, and so much more. Analysts forecast that every two years, the amount of information created is doubling and size of data are sets increasing. The Internet of Things is expected to create over 400 zettabytes of data by 2018, according to v3 technology news. Of course, the data is only as good as the insights it provides and the incremental value derived from it.
Do you know the best way to visualize your data? How do you quickly go from terabytes of data to a visually appealing dashboard to explore that data? With Big Data, this is an even bigger challenge. For everyday business users who aren’t well versed in the “rules” of analytics, the task can be monumental.
Needless to say, it is absolutely essential to transform data into the right visualizations so users can gain deeper insights and make better decisions.
In academia, smart analytics is defined as the process of collecting and analyzing data to help businesses make better decisions about their products, and services. However, people in business will tell you that it’s really about having the right information, at the right time, and in the right format to enable executives to make informed decisions.
Let’s look at some ways to represent data:
- Tabular data: When you need to know exact numbers presented in rows and columns with summary information, a tabular format can be the way to go. However, it is not conducive to helping the reader find trends and interpret large sets of data.
- Charts: Bar graphs, pie charts, and line charts offer the ability to compare data over time and analyze trends.
- Histograms: Understand frequency distribution—showing the number of observations for a particular variable at a given interval.
- Scatter plots: The scatter plot shows correlation between two variables and how they track against one another—directly or inversely.
- Cartograms: For geographical and geospatial information, a cartogram is frequently used for comparison of a variable across a map or layout.
These are just a few examples of the options available to an analytics user. However, for non-analytics experts, discerning the right type of data visualization to select can be very time-consuming and daunting.
Spotfire 7 offers new, built-in intelligence that makes suggestions on the most appropriate visualization to best represent your data. This smart wizard does all the background work so you don’t have to—making it easier and faster for the end user to be effective in their analytics process. As you select more data, recommended graph or chart selections update automatically to reflect best practices for your chosen data, so there is no time wasted in trial and error.
With Spotfire 7, even non-expert analytics users can become a “data hero” and impress their audience with awesome visualizations.