Systems | Development | Analytics | API | Testing

Imagine the following hypothetical scenario: in a rental property management system, Employee A starts editing contact info for Rental X, adding some extra phone numbers. Around the same time, Employee B notices a typo in the contact info for exactly that Rental X and performs an update. A couple of minutes later, Employee A updates Rental X’s contact info with the new phone numbers, and … the update fixing the typo is now gone! That’s definitely not great!

Learn how 29 companies are using OKRs for company and department goal-setting and accountability.

A casual stroll through recent tech headlines in the past few years makes two things abundantly clear: investment in AI is at an all-time high, and companies really struggle to get value out of AI technology. At first glance, these ideas seem to be at odds with each other: why consider investing in a field that hasn’t lived up to the hype? If you dig into the details, you’ll notice that a gap exists between the development and production use of AI in many companies.

Success in today’s high-velocity business environments means having the correct information to make the right decisions at the right time. As marketplaces grow more competitive and customer expectations continually rise, the “right time” is often real-time. Every transaction generates a plethora of data. Anomalies within your company’s data set can represent opportunities and threats to the business.

Microsoft’s.NET Framework is incredibly popular, and its widespread use is one of the reasons C# is gaining ground as one of the most popular and most-used programming languages. What’s more, .NET Core, a modular, open-source (check out the code on GitHub) development stack that’s already used by ASP.NET and.NET Native, is quickly gaining speed, which will heavily influence the demand for top.NET developer skills.

Many companies are now strategically using their data assets as the core of their digital transformation efforts. Building a data pipeline can help companies combine information from all their systems to gain insights into their business. A recent study showed that 59.5% of corporations using advanced analytics saw measurable results. Using a warehouse such as Snowflake can help companies leverage this information to drive business strategy.

Integrating Snowflake with MS SQL Server is a common situation we see here at DreamFactory. This article will break down exactly how to integrate MS SQL server and Snowflake and what are the benefits of the integration.

We are just over one week until the UN Climate Change Conference of the Parties, COP26 convenes in Glasgow. As governments gather to push forward climate and renewable energy initiatives aligned with the Paris Agreement and the UN Framework Convention on Climate Change, financial institutions and asset managers will monitor the event with keen interest.