About a year ago (March 2020) We needed a line chart that can do the following:
Allow the viewer of the report to change the Y axis scale on the fly
Allow the X axis to be placed near the top of the chart
Have the ability to invert the Y axis*
When we started, we didn’t want to reinvent the wheel, so we searched first but couldn’t find a chart on the App Source marketplace that could do all of these thing I listed above*. So we started creating our first custom Power BI Chart Visual: CHARTURO
A new Small Multiples visualization feature has been released for public preview in Power BI. I was thrilled to see this first announced on the roadmap and am looking forward to putting it through its paces now that it is out in preview.
“Small Multiples” use multiple similar views to show different partitions of a dataset. Small multiples are sometimes called trellis or grid charts and until now, you have had to use custom visuals or some SVG tricks to get the functionality in Power BI. Continue reading “Power BI Small Multiples Preview Feature”
We are happy to announce that in December 2020 Mi4 released an update to theProduction Review Dashboard with new features and functionality. Thisdashboard is available to all Productioneer customers andallows oil and gas organizations to efficiently aggregate and analyze oil and gas production across a diverse collection of assets quickly and efficiently in one report.
The Production Review Dashboard offersoil and gas companiesa modern dashboarding tool without procuring any software licenses orbuilding it in house.
Date and time values have been the bane of programmers’ existence since Pandora opened a box several millennia back……at least it feels that long. I wanted to share with you how we implemented flexible date parameters for an Azure Data Factory pipeline in a recent project.
Productioneer has an extensive paginated report library for our customers to utilize. We have everything from simple data exports to paginated reports that highlight variances and trends.
One of the reports we have had in our library for quite a while, is the Tank Stock report. The user selects a day and the report returns the tank stock and tank production for each tank in the organization for the selected day. It aggregates the stock and production at the tank, battery, field, and organization level and provides the tank strappings (feet and inches) for each tank. It is a standard and widely used report and I know it has not had any significant changes requested to it for at least 3 years.
Disclaimer: Mi4 is not affiliated with Enverus. Mi4 does not endorse or recommend any particular data subscription service.
Mi4 has helped many of our clients integrate data from data subscription services into their own projects and data initiatives. One of the many subscription services we have implemented solutions around is Enverus Drillinginfo’s Direct Access API. The Direct Access API allows Enverus customers with DI Plus subscriptions to access Enverus’ extensive collection of public data and bring it in-house.
TL/DR: Check out our C# Classes and SQL scripts for the Enverus Drillinginfo Direct Access API on our GitHub.
As an end-user of a Power BI report, a chart that looked great at first might look not so great once you start applying filters or using slicers. Very large values in the data might throw off the scales and now your line chart might be suddenly all squeezed at the top or the bottom. Does any of the above sound familiar?
Usually it’s the report designer who has all the power, this article is about giving more power to Power BI end users…
End users’ ability to change the scale, appearance or formatting of that chart is limited. That’s why I started creating the Mi4 Line Chart Power BI custom visual that lets you switch scales on the fly, and eventually have more overall control of the visual without having to edit the report.
As we wrote about earlier this month, the Texas Railroad Commission (RRC) released a treasure trove of data freely available to the public on their site. It was like Christmas in the Mi4 office. After we sang some carols and drank some hot chocolate, we realized that there was so much data. We didn’t know where to start.
Christmas in September
As my colleague @Talal wrote last week, we decided to get Lat/Long coordinates for every Texas well. In his post, he explained, there are many use cases for this data, so it seemed like an excellent place to start.