In this document
We will teach you how to work with the Analyst application and what is the general workflow.
The Analyst project workflow
The steps you follow in the application depend on whether you are opening an existing project or creating a new one:
Existing projects typically have datasets already imported and may have some quality checks completed. You can review or continue these processes as needed.
New projects require you to complete all workflow steps from the beginning, including data import and quality checks.
This guide covers the full workflow for new projects. The process for existing projects is similar but may start at later workflow steps, depending on the project's current progress.
Opening a project
When you launch the application, you will be prompted to choose one of the following options:
Open an existing project: Select this option to work with a project you have previously saved. Just select the project you want to open and click the “OK” button.
Open the Demo project: The Demo project is included with Analyst and acts as a sandbox environment. Use it to explore features and learn to operate the application without affecting your own data. Select the “Open demo project” option and click “OK” to open it.
Create a new project: Choose this option to start a new project from scratch.
Tip: Use the Demo project to become familiar with Analyst workflows before starting work on your actual projects.
Starting a new project
If you want to create a new project, proceed with the following steps:
Select the “Create new project” option in the Getting started pop-up.
Click the “Browse” button and:
Navigate to the new project folder (or create a new).
Type the name of your project in the File name field of the explorer.
Click the “Save” button to apply the changes.
Click “OK” to create the project.
After you confirm with the “OK” button, you will be prompted to create a new database for the project. You can cancel this step if you want to allocate an existing database to this project later. Confirming with the “Create” button will create a new, empty database and allocate it to the project.
Tip: Do not create projects in the default SDAT folder. It contains configuration and log files which are removed during uninstallation process along with its it's content. We recommend creating a custom folder outside of the AppData category.
Setting up the project datasets
After creating a new project, the first essential step is to import and configure the necessary datasets. Use the Database manager to perform this task:
The Database manager lists all databases previously used in the application, along with their associated datasets.
You can review available databases and select the datasets required for your project.
For detailed instructions on setting up a database and selecting datasets, refer to the Database setup documentation.
Importing new datasets
If you need to add more datasets or include additional time periods to existing datasets, use the dataset import feature:
The dataset import wizard helps you process data from different sources, which may use varying parameter names or data structures.
The wizard provides tools and parameter adjustments to ensure that your data is prepared correctly for use in Analyst.
For step-by-step instructions on importing and modifying datasets, refer to the Dataset import guide.
Editing existing datasets
Imported datasets do not always fully comply with the Analyst data structure and changes need to be made to make it compatible. You can use the Metadata editor to perform these changes and update the dataset:
The Metadata editor allows you to fill in missing values, change parameter names, or make other edits.
You can update parameter names, adjust dataset properties, and ensure compatibility with the current application standards.
For detailed instructions on using the Metadata editor, refer to the Metadata editor guide.
Important: Please handle this tool with caution. Inaccurate metadata can significantly affect automated quality control processes, as well as affect calculations and visual outputs in the Solargis Analyst.
Quality control checks
Raw data, such as ground measurements, often contain inconsistencies or invalid values that can affect analysis and simulation results. Performing data quality control (QC) is essential to obtain reliable and accurate datasets. Analyst provides several quality control options to help you identify and correct these issues:
Time reference check: Verifies that your dataset’s time reference matches the intended periods and that any time shifts are correctly defined.
Automatic solar and meteorological data checks: Detect and flag common data anomalies.
Interactive (manual) data checks: Manually review and address data inconsistencies.
Automatic post-filtering verifications: Run additional checks to clean up data after quality control.
For step-by-step instructions on each QC procedure, refer to the guides available in the Quality control documentation category.
Data visualization and analysis
Once your data is prepared and cleaned, you can visualize and analyze it using the visualization tools available in Analyst:
Heatmaps: Visualize spatial or temporal data distributions, allowing you to identify patterns and anomalies across datasets.
Histograms: Examine the frequency distribution of variables to detect common values and outliers.
Monthly and yearly averages: Explore aggregated data over time intervals, supporting seasonal and long-term analyses.
Charts for trend and extremes analysis: Analyze trends, detect extreme values, and compare datasets using line charts and other graphical representations.
All visualization tools in Analyst are interactive and highly configurable:
Adjust visualization parameters to focus on specific data ranges or time periods.
Filter and segment datasets to match your analysis objectives.
Export visualizations for use in reports or for further offline examination.
These tools enable you to perform detailed analyses tailored to your requirements, making it easier to interpret results and support decision-making throughout your project. More information about how to work with the visualization tools is provided in the Analysis documentation.