Ananas Analytics

It goes without saying that not all those who use computers at their jobs are tech-savvy people or have advanced technical skills.

When the inexperienced need to work on a project, they can turn to specialized apps that can make their tasks easier. Such a solution is Ananas Analytics, a dedicated visualization and integration utility.

When you first run Ananas Analytics, you might be overwhelmed by how many types of elements it supports, along with their customization options.

Nonetheless, you can download some examples, and you can take the time to explore them until you fully understand the functions.

Basically, you only need to drag and drop the elements you need onto the dashboard, then configure each one according to your necessities.

All the supported elements are grouped according to their functionality: Source, Transform, Destination and Visualization.

So first of all, you need to define a source, for example Web API, CSV, Excel, JSON, Google Cloud, BigQuery table, PostgreSQL or MySQL databases. After you selected and analyzed the data, you can move on to the next stage.

You can transform your data with SQL, join two datasets, concatenate them or transform the data with Javascript.

This is the point where you are required to choose a destination for your project. You can select between a CSV file, PostgreSQL or MySQL databases, or upload the data to Google Cloud storage or BigQuery.

When it comes to visualization, several variants are available: line charts, bar charts, pie charts or big numbers.

The best way to fully understand and appreciate the plethora of features and customization options that Ananas Analytics has to offer is to launch it. You can also browse the detailed User Guide if you want to go more in-depth.