During the webinar, Doug shared his experience conducting his first machine learning study with our company. One of Doug's key points in the webinar was how pleased he was that the machine was able to find a mix of known and new insights. Doug stated that the combination of finding things he already knew and identifying new insights, "increases both [his] confidence in the validity but also the value" of machine learning. The known insights that the machine picked up on were reassuring, demonstrating to our client that the machine could correctly identify key themes related to snow removal. In turn, these confirmatory findings strengthened Doug's confidence in the new insights he was able to collect, because the machine had demonstrated its accuracy.
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Today in Build 2017, we released Microsoft's contribution to the Open Source Community by extending Zipkin with the power of Application Insights (AppInsights) calling it "Zipkin-Azure". Zipkin is a tracing tool for distributed systems to log events related to each individual activity (also known as job, transaction, or trace, depending on the context) in a way that allows the path of the activity through the system to be reconstructed. It offers correlation across multiple services within a customer's application. With AppInsights integration, Zipkin now gains the ability to log data to an Application Insights store and to trace activities through multiple services including non-logging systems using impersonation. It provides application performance management features from AppInsights along with tracing capabilities provided by Zipkin.
The strategy to turn the raw data into actionable insights is to integrate and analyze data from all data sources to reach better and optimized business decisions. The word "big" in big data refers to the huge volume of data involved. Big data technologies aim at storing, analyzing, querying, and updating large chunks of data coming from different areas. It is important to turn this massive amount of data into actionable insights to obtain better decisions for companies. Actionable insights are created by analyzing processed data and drawing conclusions.