From Data to Insight

Your analysis is only as good as your data. Therefore your first step is to get your hands on the data. If the data does not exist, then the first step is to start collecting it, but here we'll assume that the data exists somewhere.

Data Sources

Data can be found in various places. Let's review these places and the strategies that you can employ to access this data.

Databases

A lot of useful data live in databases. Explore Analytics makes is easy to access data directly from the database regardless of whether the database is in the cloud or in your private network. To setup a database in Explore Analytics, you'll need to have some basic information about the database including the server name or network address, and a username and password that's used for connecting to it. For now, we won't worry about the setup details, as they are explain in great detail in the section "Configuring a Data Source".

There are some cases however in which connecting directly to the database is not possible and another strategy is required.

Application Data

Many applications use a database to store their data, but discourage or prohibit direct access to this database. That's because the application manages data access and has rules about piecing data together from the database and applying security rules. Direct access to the database may yield data that's not usable outside of the application.

Here are your typical options for access to application data:

• Application Programming Interface (API). Modern application provide Web-Service APIs for data access. Explore Analytics can utilize such APIs to access the data through the application. Examples of such applications include ServiceNow and Salesforce.com.
• Data Export. Most applications allow you to export data into a file. You can then upload and import such files to Explore Analytics. You can relate multiple files and use them in your analysis. You can periodically refresh these files to update your analysis with the latest data.
• Data Warehousing. Some applications provide a business-intelligence warehouse. They automate the process of exporting data that's useful for reporting and placing it in a database where business-intelligence tools such as Explore Analytics can access.

Spreadsheets

The data needed for your analysis may reside in spreadsheet files. Such files are pervasive in organizations and they may contain valuable information. Although spreadsheet programs such as Excel can be used for data analysis, a better solution is to import these spreadsheet to Explore Analytics. Here are some benefits of doing so:

• Combine data from multiple spreadsheets in your analysis.
• Create reports once and refresh them with new versions of your spreadsheet.
• Share data and analysis securely.

Explore Analytics makes it very easy to import spreadsheets from file or from Google Spreadsheet.

Public Data

Increasingly, data is made available to the public by governments, universities, and various organizations. Such data can be imported to Explore Analytics and combined with your data in the analysis to gain more insight.

Big Data

Large data sets, too large for conventional databases or single servers, are the result of collecting detailed information about customer interaction, for example. New technologies are available for crunching through vast amounts of data using arrays of severs and techniques such as MapReduce. Once reduced, Explore Analytics is a great tool for visualizing the data and turning it into insight.

Drawing Insight

Once we have the data, we can begin the process of drawing insight from it. The traditional approach to data analysis assumes that you have intimate knowledge of your data and therefore you know exactly which fields to use and what calculations to make. Explore Analytics, however, was designed not to make that assumption. As the word "explore" in its name suggests, the product assumes that you begin by exploring the data and discovering the fields and calculations that would yield the desired insight.

Exploring Data

The Pivot view in Explore Analytics is designed to easily discover the useful data groupings. It's easy to count the rows in a table, group by one field or another including fields in related tables, to see possible field values, and to group by year or other time periods. The timeline chart makes it easy to see data over time and the map chart makes it easy to see geographic data distribution. In the following pages we'll discuss in greater detail how to use Explore Analytics to get to know your data and proceed to draw insight.

Visualization

Humans are good at processing large amounts of data visually and detecting patterns, trends, and relationships. Visualization allows you to pack a lot of information into a visual that tells the story behind the data. In practicality, it’s a process of trial and error in which you try various types of visualizations until you find the one that best tells the story. Explore Analytics makes it easy and quick to create visualizations and modify them to facilitate the exploration process and focus your time more on the data and the insight and less on making the tool do what you want.

⇦ How does it Work

⇧ Table of Contents

⇨ Preparing to Explore