In the third instalment in her series about the best practices and procedures used in the management of database systems, Victoria Holt takes a look at the results and findings of her analysis.
Last month, we hosted a three-day long, MVP-led TechDays Online. All 18 sessions are available to be viewed on-demand via Channel 9, so don’t miss out on topics including bots, Linux on Azure, Xamarin, Quantum Computing, IoT and more!
Say hello to the TechNet Pod! Our new monthly podcast will roundup everything that’s been happening on Microsoft UK’s technical channels, including TechNet UK, @MSDevUK and @TechNetUK.
As a preview for his upcoming talk at TechDays Online 2017, Gary Pretty takes a look at the Microsoft Cognitive Services API and what you could be using it for. Remember to register today!
This article is for those new to the world of business intelligence, such as application developers and cloud architects, who want to understand how a typical BI solution works, what each of its components do and some of the technologies used to implement them.
In the final article of their three-part series, SoftServe’s Data Science Group (DSG) wraps up their look at informational security risk identification by detecting deviations from the typical pattern of network activity.
Continuing the previous research on Machine Learning: Achieving Ultimate Intelligence, SoftServe’s Data Science Group (DSG) describes informational security risk identification by detecting deviations from the typical pattern of network activity.
Machine learning techniques may be applied to solve a whole range of problems, and today we take a look at some of the more prevalent examples out there.
How do customers feel about your company? It’s probably not the easiest question to answer definitively. Data analysis is often the best step, and it’s qualitative data that can often mean the difference between success and failure.
Big data can be used in the strangest of ways and the retail industry has usually been the heaviest user of all. Rick Delgado shares four wise practices that convert raw data into satisfied customers, improved products, and notable profits.