Documentation

Analyzer

datapine’s Analyzer helps you to create actionable insights based on the data that you have connected and then saves these information as professionally designed charts and graphs on your dashboards. No matter how strong is your technical experience, datapine will provide you instant and easy access to all the information that you need to make smart business decisions.

 

In this section, we will introduce you to the Chart Creator and demonstrate how to create your first chart in datapine. You will get to know all the different visualization types in datapine and learn how to build your own custom fields and metrics. More advanced users might also want to discover the SQL box to run own SQL statements directly in datapine. Let’s take a closer look at the different parts of our analyze section.

 

 

1) Chart Creator

 

Here, you will learn how to use the Chart Creator to build your charts and graphs and find useful information about the chart types and style options in datapine that helps you to get the most out of your data. The right type of visualization helps you understand and analyze your data better, and allows you to reveal actionable insights about your business in just a few seconds. The Chart Creator is where you start building your own dynamic dashboards and empowers you to create insightful charts and graphs with simple Drag & Drop.


2) Metric builder

 

In this section you will find useful information on how to create customized fields, build cross-data source metrics and how to visualize your custom metrics in datapine. While our intuitive Chart Creators interface is perfect to visualize your data, you might also want to add some calculations or perform some more advanced analytics within datapine. The Metric Builder is a great function to easily setup customized fields and create new columns by combining two or more fields from your data sources. You may easily build cross-database metrics using simple mathematical expressions, add custom names and leave notes for other team members to explain your custom formulas.

 

3) SQL Query Box

 

This subpart of the Data Analyzer provides the basics about the SQL Box, and gives you some hints and tips on how to work with SQL Queries in datapine. The SQL Box is a great feature for advanced users with good SQL skills to visualize and automate any of the SQL Queries that have already been in place for the weekly or monthly reporting. Use the native language of your database to run the scripts directly in datapine and visualize the results with ease. Thanks to our data warehouse you may also run cross-database queries and merge your results with data from other sources.


4) Visualization Types

 

In this section, we will introduce you to the different visualization types in datapine and demonstrate how to customize and edit your charts and graphs. The right type of visualization is crucial to make your dashboards visually appealing and understandable to your audience. Choosing the right charts and graphs for your data will help you to extract hidden insights or highlight trends, dependencies and outliers in your data. In datapine, we offer various chart types to help you visualize your data fast and easy.

 

 

5) Formatting

 

In this section, we will introduce you to the chart formatting options in datapine’s Data Analyzer. We show you how to apply different formats to your charts including labels, colors, axes and trends. When creating charts and dashboards you need to make sure that your data is presented in the right format so that it is easy to understand and fits into your story.

 

6) Merge Data

 

In this section you will learn how to create charts from multiple data sources, how to change the join type when querying your data sets in datapine and how to merge chart types with just a few clicks. Being able to merge and unify your data means to access a full new level of insights and information that you can take into consideration when making your business decisions. In datapine, you can easily combine information from different data sources and even apply multiple visualization types to one chart to gain the insights you are looking for. Before you can start merging your data you should know how to define the relations between your dispersed data sources and what to keep in mind when cross querying your data.

 

7) Transform Data

 

In our Data Analyzer, we offer a number of options and functions to transform and enrich your charts and graphs with no effort. We will demonstrate here how to sort, split, group, limit and accumulate your data. You will also learn how to apply conditions and filters to individual charts before saving them to your dashboards.