Bringing data together from different sources is how data adds value to the decision-making process. In the real world, the data you need usually won’t sit neatly in a predefined database inside a fully prepared data table just waiting for you to access it. In most cases, data must be obtained from different sources to add the depth and wide scope necessary for the best possible analysis and decision making.
Related: Read how one analyst got her feet wet in analytics. Don’t miss the advice from Sean Adams about focusing on defensive design, because “the data is always going to be shit.”
Finally, here are the most common types of data you will find when performing everything from basic to complex data analysis.
Five Types of Data
A string represents alphanumeric data and can include letters, numbers, spaces, or other types of characters. A string can also be thought of as plain text. All the characters in a string are considered text even if the characters are digits.
There are several different numeric data types, including integers, decimals, floats, and doubles. Numeric data types do not have adjustable lengths except for Fixed Decimal.
Date and time data is what it sounds like, though its format can look a bit different. You may have a 10-character String in “yyyy-mm-dd” format for a date or an 8-character String in “hh:mm:ss” format for time. Or, you may have DateTime information that looks something like a 19-character String in “yyyy-mm-dd hh:mm:ss” format.
Example: December 2, 2005 = 2005-12-02, 2:47 and 53 seconds a.m. = 02:47:53, 2005-12-02 14:47:53
To start, it’s helpful to know that Bool is an expression with only two possible values.
Example: True or False where False equals 0 and True equals non-zero.
The spatial object associated with a data record. There can be multiple spatial object fields contained within a table.
Example: A spatial object can consist of a point, line, polyline, or polygon.
The simple fact is that the best decisions will be made only when all the relevant data is available for analysis. The key data almost always comes from multiple data sources and often comes in different formats. Knowing all the formats, categories, and types of data is one of the first steps in diving into analyzing. Find an analytics platform that allows you to blend any format of data from anywhere so that you can solve any problem, any time.