Waterly

The Water and Wastewater treatment plant is an ever-changing field with multiple players. These individuals are each interacting with the flows, analyzers, samples and much more. These data inputs coupled with the potential for necessary adjustments due to water quality fluctuations on a daily, or even hourly basis, can create a data noisy environment. Understanding which data point was entered when and by whom is important. Also, examining the entries made throughout the day can provide stability and confidence in treatment operations, while allowing time to adjust if necessary. 

 Waterly continues to help reduce this noise and bring structure to the data inputs. We do this in multiple ways. One is a comprehensive Audit Log (Audit Log article) of every data event and type in Waterly. We have now developed two more ways to bring these critical insights to operators and Water/Wastewater professionals: Audit-by-metric and Interval History.

Audit-by-metric

This new tool allows for each individual metric to be audited with a full log of data entries. The date range for this audit log can be filtered for one day up to 60 days. This log is available for all metric types. This log is accessed by clicking the scroll icon next to the metric. Once clicked, all the data entries for that singular metric are displayed. The information available in this log is identical in format to the comprehensive Audit Log.

The list of items that appears in the Audit table has four columns that correspond to the records in the audit log:

• Time Saved to Waterly - Records the date and time and time zone of when the event of saving the data occurred in the local time of the source site. Note that the timestamp here is created when a Waterly user received the “Saved” notice in the app.
• Type - The “DataPoint Changed” event in the log refers to the type of event displayed. This is the most common event and the only type displayed in this feature. A blank metric that has new data entered will display [Empty] → [New Data]. 
• Event- The Event column is more of an Event Details column that stores lots of information about the event, including:
  1. What Report Date (and/or time) was the change made for?  This should usually be the same as the (Date) and Time Saved to Waterly.  However, if users are “backdating” entries, you will see the first column will have a date different than the report date it was applied to.
  2. The data hierarchy of where the change was made in Waterly.  You can click on the box with the arrow to open a new tab with that site.
  3. Event Details - that list the old value, the new value, as well as many of the gory details of exactly what, where, when, and how the data change was committed to the Waterly database.  This information is usually used by system administrators to troubleshoot the details of the application.
• User - This is the user who was logged in when the change was made.  You can hover over the entry if the name is truncated. The water drop icon indicates the data was entered automatically by SCADA or a WaterClick Partner. 

The Audit-by-metric feature will allow all users to see what and when the data for each individual metric was entered by whom at the click of a button. 

Interval History

Some treatment facilities maintain multiple shifts collecting data in selected intervals throughout each shift. These time-defined data entries are known as interval metrics. Until now, the best way to review the data for a day’s intervals was to click through each hour. This was time consuming for operators sharing data. We heard the need to see the history of each day’s data entry for each interval metric. This will provide the ability to gain needed insights into fluctuating water quality through the day. 

Now it’s even easier to examine the data entries for each interval metric. By simply clicking on the stopwatch icon⏱️in front of each interval metric, a user can open a new information box. This box displays the assigned intervals, and the data entered (if any) at each and every interval. This easy-to-use tool provides a quick way to assess the state of treatment at any time for interval metrics, i.e. the beginning of each shift, throughout the day as adjustments are made. 

In this example, it’s easy to see the flow has varied between a high of 1.647 to a low of 1.436 throughout the day. The Metric History feature provides users at a facility that utilizes interval data entry a simple way to see data over the period of an entire day, without navigating to a report.

Conclusion

With these two new tools at your fingertips, Waterly has just handed more visibility to operations teams. At the click of a button any user can see the entire data entry log of a metric since it’s creation and all data entered across each interval through a day.  With wise use of these features, diagnosing adjustments in treatment becomes even easier, communication across shifts increases, and daily fluctuations in water quality are readily apparent.