Data, Analytics, AI, Business Intelligence posts and videos
Natural Language Query is a key part of a new wave of innovation. If you haven’t seen it, the Power BI Mobile App for iOS has a Virtual Analyst built into the tool. Voice recognition along with Quick Insights is laying the groundwork for a future in which we can talk to our data analysis tools. Click here to learn more about the Power BI Mobile Virtual Analyst, or check out the video below:
It seems obvious that hot weather increases heat related Emergency Room visits. Based upon an upcoming weather forecast, can you predict the number of patients that an ER should prepare to see?
Minneapolis and Buffalo are both famous for their Winters. But how do their Winters compare? Which city gets more snow? Which is colder? GNet Group’s Climalytics empowers you with the ability to combine your own data with weather data in order to discover new value.
Slice, dice and visualize United States historical economic data including GDP, Federal Deficit, M2 Money Stock and more using Power BI to mash data up from the web. Visualize how trends and relationships are changing over time. Explore the impact of the 2008 economic crisis and beyond.
FEMA (Federal Emergency Management Association) provides an API that can access data about disasters going back decades. This video walks through a video that uses Power BI to access that data and visualize it for new insights. View disaster data from the 1950s, Hurricane Katrina, and even the recent Flint Michigan water issues. Use Power BI to slice, dice, and drill into data with ease.
Have you ever wondered how Unemployment trends would compare to other measures such as GDP and National Debt? Walks through a Power BI report that mashed up labor force data with other metrics to find new insights. Slice, dice, and drill into the report to understand employment data trends over time.
Pull Stock Market ticker data into Power BI using APIs, and mash the data up with additional economic indicators for analysis. Visualize the Daily Averages vs 50 day and 200 day Rolling Averages to find the hypothetical “death cross.” Slice, Dice, and Drill into the data with ease to find new trends and relationships.
Ever wish you could compare Stock Market Data with GDP, National Debt, Unemployment Data, Gas Prices, FEMA data, and more? All of the data used in this demo is pulled from public websites, public files, and Open Data APIs. The purpose of this demo is to show the value that Power BI can provide using interactive visualizations built with data pulled together from different sources for comparison. With the exception of an Excel file to populate a Date Dimension and a Rollup Category, all of the data is pulled from web sources without using a data warehouse or intermediate staging tables.
A post affiliated with this video was on a blog which has been decommissioned. A version of that post can be found at the WayBack Machine: https://web.archive.org/web/20190615151622/http://blog.gnetgroup.com/bi/2015/06/03/webinar-rise-of-the-machine-learning/
An article with links to documentation about this video was published to a blog that has been decommissioned. A version of that blog post can be read at the WayBack Machine: https://web.archive.org/web/20150129142611/http://blog.gnetgroup.com/bi/2015/01/06/predict-breast-cancer-biopsies-for-malignancy-using-azure-machine-learning-azureml/