Featuring report development in Power BI Desktop and publishing reports to Power BI Service

Final Power BI Report using Push dataset.
Final Power BI Report using Push dataset.
Final Power BI Report using Push dataset. Image by author.

Welcome back to the final part of the Minimum Viable Streaming Dashboard series.

In this post we’ll cover how to build a Power BI report, using the Push dataset we created back in Part 2.

To refresh your memory, we currently have an Azure Stream Analytics (ASA) job running in Azure cloud that is writing events to a Power BI Push dataset.

Featuring Push datasets and the Power BI REST API

Welcome back to Part 2 of the Minimum Viable Streaming Dashboard series, where we continue our discussion on real-time dashboards and how to configure them in Power BI.

Back in Part 1, we talked about Streaming datasets and how they utilize a temporary cache to store data. The data expires quickly, causing historical data analysis to be impossible.

In this post, however, we’ll be exploring how to configure a Push dataset instead. And you’ll see that a lot more functionality becomes available to us — the report consumer, including filtering, tooltips, drill-throughs, and more.

Pushing Data to the Power BI REST API

Power BI Rest API

Pushing data to a Power BI…

A trilogy about developing real-time streaming dashboards and their use cases in Power BI.

Traditional dashboard. Image by author.

Most of us are familiar with the idea of a traditional dashboard, a compilation of key metrics and charts, displayed to provide useful information for decision-making.

Majority of these dashboards are powered by underlying datasets that refresh at scheduled intervals (weekly, daily, or hourly).

At any given point, the dashboard is providing you with a snapshot of static information that will be refreshed sometime in the future. And this design pattern is proven and ubiquitous.

From time to time, however, there comes a demand from stakeholders for dashboards with the capability to display data generated a few minutes, or even…

A piece featuring why work as a data analyst can lose its meaning.

Grave of Data Analysts.
Grave of Data Analysts.
Grave of Data Analysts. Photo by Kenny Orr from Unsplash.

In my recent post, Data Analyst Primer, I elaborated on how demand for data analysts is growing and highlighted the steps you can take to get a foot in the door, and land that first entry-level job.

The purpose of today’s article is to offer a different perspective, a pessimistic view discussing why work as a data analyst can feel meaningless.

Often, expectations of a dream job deceive us. There are plenty of unpleasant responsibilities analysts have to carry on their backs, that separate what appears to be an ideal career, from the actual reality of the situation.

The Dunning-Kruger Effect for Data Analysts

Unskilled and…

An essentials guide for aspiring data analysts, priming you with the key skills you need to know to become one.

Data Analyst Summer Internship
Data Analyst Summer Internship
Data Analyst Summer Internship. Photo by Ethan Robertson on Unsplash.

Back in the summer of 2018, I was just starting my first internship as a Data Analyst.

Data science was all the rage back then, with the data scientist being heralded the sexiest job of the 21st century. I remember reading articles featuring the famous Venn diagram that described what a data scientist was.

In hindsight, the Venn Diagram wasn’t very descriptive, but it provided a starting point to pick up the tools and knowledge that would eventually help me launch my career as a data analyst.

Nathan Cheng

⚙️ Full-time Data Engineer. 📚 Writer for The Startup and Towards Data Science (TDS). linkedin.com/in/nathancheng-data/

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