Historical Data
Use the graphical database viewer to visualize your measured values.
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Use the graphical database viewer to visualize your measured values.
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Datacake has a database viewer that allows you to view and compare sensor data from your sensor. We also call this viewer the history of a device.
To open the history view, navigate to the history tab using the tab bar on the device view.
You will see the following view.
When the history view is opened for the first time, no fields are selected yet to be visualized.
To be able to select fields, please scroll further down. There you will find a list with all fields of the database.
Now select the respective fields that you want to display on the history and simply click on the checkbox next to the respective field.
If you now scroll up again, you will see that the visualization in the form of a chart for the respective fields is now displayed.
Using a drop-down, predefined time ranges can be selected for the display of the data.
Alternatively, individual time ranges can be defined. To do this, simply click on the text box that displays the current time range. A window opens for the graphical selection of a time range.
You can use both the previous and next buttons next to the time range input field in order to jump to the next or previous time range.
This works great if you for example have selected a time range preset like day, week or month and if you want to jump between days, weeks or month.
If you have selected a custom time range these buttons will skip to the amount of time (and date) defined in the time range selector.
The resolution defines the time intervals with which the data is queried by the API over the specified time range.
The settings are defined as follows.
This works in a way that the Chart requests at least as much datapoints from the backend as pixels are available on the screen.
You can override the automatic resolution setting by specifying your own resolution. However, there is a maximum number of data points that can be retrieved from the backend to protect our API limits.
So, if you selected the period of one year as an example, and set a resolution of 1 minute, the number of data points would lead to several million per selected field.
Even if our servers were able to provide this number of data points, it does not make sense to request such a large amount, as the graphical representation will not have enough pixels on the screen to display it properly. So data points would be thrown away anyway.
If you select a resolution that is lower than the transmission frequency of your sensors, then all data points that lie within the resolution are combined and an average is formed.
As an example think of a sensor that sends every 5 Minutes and a Resolution set to 1 hour, this makes:
12 Messages per Hour
Average our 12 Messages = 1 Value for Resolution of 1 hour.
In the following screenshots, you can see the effects of the resolution.
The first screenshot shows you a setting for Auto-Resolution. There are more pixels on the screen available than data points for the selected fields so the backend fills all pixels with repetition of data points.
The time range is set to one week and the Sensor sends about every one to two hours generally with shorter intervals on steeper value changes.
You can clearly see the quantization effects.
No averaging is applied here as there is more space than data points.
Now in the following screenshot, you see the same time range as above but with a resolution set to a manual value of 1 hour.
As most of the time, the sensor sends every one or two hours, there is still no averaging applied (no interpolation) but you can see that the quantization does look different. There are now less datapoints than pixels still but there is no fill happening.
The filling of gaps works in conjunction with the resolution. To explain how it works we select the following settings:
Time range 1 week
Resolution set to 30 Minutes
As long as the filling of gaps is enabled you see a full line chart.
Now, if we deactivate the gap-filling option (which is enabled by default) we can see a change happening.
You can see that the chart is no longer fully displayed and only a few areas show a chart. What does this mean?
Remember that we have set the resolution to 30 minutes. If you uncheck the "Fill Gaps" option, all areas where there are data points with a time span greater than 30 minutes will be hidden.
This means that the chart above shows only the area where there are data points whose time span is less than or equal to 30 minutes.
Above the table for selecting the fields to be displayed on the history, there are additional column headers, which show you statistics for the respective fields.
The following statistical information is available for each field.
Current Value
Average
Minimum
Maximum
The time range for each statistic (average, maximum, minimum) is defined by the time range of the history.
If you hover over a Maximum or Minimum Value you can see the time this event has occurred.
If you see a "No Data" tag or "null" sign on the list of fields this means that the field has not yet received any data or the decoder has not yet stored any information on that field.
The "Download as CSV" feature in our portal allows users to easily export their data as CSV files. This documentation guide will walk you through the process of utilizing this feature, ensuring you can extract the data you need in a format that is compatible with external applications and analysis tools.
To begin, navigate to the History View in the portal. This view displays your data in a chart format, providing an overview of the selected timeframe, resolution, and fields.
Make sure you select the fields you want to export. The data that is considered for being exported matches the configuration of your history view.
Within the History View, you will find a distinct button placed adjacent to the text. This button is specifically designed for downloading your data as a CSV file.
Click the designated "Download" button to initiate the process of generating the CSV file. The system will automatically extract the data corresponding to the selected timeframe, resolution, and fields from the History View.
Once the CSV file is generated, it will be downloaded to your device. Depending on your browser settings, you may find the file in your default download folder or a location of your choice. It will be saved with a .csv extension, making it compatible with various spreadsheet applications.
The downloaded CSV file contains the same data displayed in the History View chart. You can use this file for further analysis, import it into external applications, or integrate it with other systems. The structure and organization of the CSV file will mirror the selected timeframe, resolution, and fields from the History View.
Conclusion: The "Download as CSV" feature empowers users to effortlessly export their data from the portal. By following the steps outlined in this guide, you can extract the data you need and leverage it for various analytical and usage purposes.
If you encounter any issues or have further questions, please reach out to our support team, who will be glad to assist you.
Happy analyzing!
