In this document
You will learn how to work with the Analyze analysis tool of the Analyst application and how to examine the data.
The Analyze tool in the Analyst application offers specific insights into your datasets and their parameters.
Key points to remember:
The interface offers several types of visualizations, separated into individual windows, to examine the data in various ways.
Zooming and moving charts is synchronized across all plots in the respective visualizations.
Filters, aggregations, and other options must always be applied using the “Redraw” button.
Zooming the chart also considers the selected height as well. You can use this advantage when selecting data range with low values which would otherwise appear close to zero in the chart.
The Analyze tool
You can open the Analyze tool from the main menu via Analysis/Analyze or by using the 
quick access icon located below the main menu.
The interface offers the following:
Visualization windows: Switch between different data representations, charts, and data comparison tools.
The visualizations plot: Various visualizations are displayed here, depending on the selected visualization window.
Parameter selector: Select dataset and its parameter to display in the charts.
Options: Filter the data, use aggregations, filters, and other customizations to display the required values and ranges.
Redraw: Use this button to apply selected filters, aggregations, and other configurations.
Selecting the dataset and parameter to analyze
You can open the Analyze tool for any dataset in the Project datasets list, and it will be selected in the plot by default. However, you can change this anytime directly in the Analyze tool. Once you select the required dataset, select the parameter you want to examine in the charts.
The visualization options
You can customize the charts and configure the visualizations to your requirements. Each data visualization method offers data aggregation and filtering options for better data examination. These are located below the compared parameter statistics window.
Aggregations, Filters, and Flags are identical for all visualization screens, except for Monthly Averages and Trends, where aggregations are not available. Additionally, there are visualization-specific options that each window offers for even better customization.
Data aggregation
The datasets are displayed in the charts with their original temporal resolution by default. If you want, you can aggregate it to a higher temporal resolution to highlight broader trends and patterns (e.g., 1-minute data to 15-minute data).
To aggregate the data:
Select the desired aggregation in the Aggregation dropdown.
Set the minimum of valid points (in percent) that must surround the aggregated value to display it in the chart. You can leave this on the default.
Tip: Do not forget to apply the aggregation to the charts using the “Redraw” button.
Filtering options
Take advantage of dedicated filters to filter your data based on your requirements.
You can filter by year/month or exact dates, depending on your preference.
You can apply a time interval to see values only at a particular time period of each day. Additionally, you can include/exclude daytime and nighttime values using the respective checkboxes.
The sun elevation filter is also at your disposal to select a period between certain sun elevation levels.
Flags filter
An additional Flags filter is provided for you to view values with particular flags only. This can be useful when you need to examine, for example, values that were flagged with the shading flag. Passed values are selected by default - make sure to uncheck them if you do not want to see them in the chart.
Note: Keep in mind that the dataset must contain flags from relevant quality control (QC) checks to use the flag filter.
Select the flagged values you want to display.
Apply filter using the “Redraw” button.
Analyzing the data in the Analyze tool
You can analyze your data using the following visualizations:
Profiles: Look at the diurnal patterns of global horizontal irradiance (GHI) with probability ranges and average values.
Multiyear analysis: Visualize the data as Time series, daily maximum of GHI, and maximum daily clearness index (Ktm).
Kt graphs: The scatter and density plots visualize relationships between solar clearness indices (Ktm, Ktb, Kt), diffuse fraction (DIF/GHI), and solar elevation.
Monthly averages: These charts display monthly GHI values across multiple years, with probability ranges (P10-P90, P25-P75, P50-median) and min-max bands.
Trends: The trends chart shows long-term daily average solar radiation (GHI) with a moving average and a linear trend line.
Profiles visualization
The default window when you enter the Compare analysis tool is the Profiles window. Here, you can examine the diurnal GHI patterns and see various probability scenarios and average values, helping you to analyze typical daily solar radiation curves, variability, and uncertainty for each month.
You can decide whether you want to see monthly or yearly averages, display average or median values, and further customize the probability scenarios visualizations.
Decide whether to show monthly or yearly values and adjust time zone if required.
Toggle display of averages and median values in the chart.
Adjust probability scenario ranges or add custom if desired.
Tip: The color legend for the chart parameters is shown above the plot.
Multiyear analysis visualization
The multiyear analysis gives you an overlook at the parameter Time series, daily maxima of GHI, and examine the maximum daily clearness index (Ktm), enabling you to assess solar resource patterns, data quality, and year-on-year variability for photovoltaic analysis.
The top chart displays the parameter’s Time series, middle chart shows maximum daily GHI values, and the bottom provides insights into the maximum daily clearness index. You can customize various limits in the provided customization options to view your data per individual requirements.
Kt graphs
These scatter and density plots visualize relationships between various solar clearness indices (Ktm, Ktb, Kt), diffuse fraction (DIF/GHI), and solar elevation, helping you to identify atmospheric patterns, outliers, and data quality in solar irradiance measurements for technical validation and quality control.
You can enable the AOD lines, that represent theoretical curves for various values of aerosol optical depth (AOD), showing how changes in atmospheric aerosols affect the relationship between solar irradiance indices (such as Kt, Ktb, and DIF/GHI); they are used for data quality control, comparison against real measurements, and to identify atmospheric clarity and turbidity effects. Additionally, you can adjust the sun elevation threshold to further customize the visualization.
Monthly averages visualization
These charts display monthly GHI values across multiple years, showing various probability ranges and min-max bands, allowing you to assess long-term solar resource variability, typical irradiance levels, and statistical uncertainty for each month.
Trends charts
The trends chart shows long-term daily GHI averages with a moving average and a linear trend line, allowing you to visualize interannual variability, seasonality, and detect possible long-term changes or drift in solar resource over time.
Customization options include:
Min of valid records for daily averages: Set the minimum percentage of valid data required for including daily averages.
Linear trend: Toggle a fitted linear trend line on the chart.
Polynomial trend and order: Optionally fit and display a polynomial trend line (order selectable).
Smooth data: Apply smoothing to the polynomial trend for better visualization and reduced noise.
Moving average & size of moving window: Enable and configure the moving average (e.g., 12 months) to highlight long-term patterns by averaging values over a defined period.
