Home PC News Microsoft launches Dataflex, a relational database for Teams apps

Microsoft launches Dataflex, a relational database for Teams apps

Microsoft at present launched Dataflex, a relational database that lets enterprise builders create, deploy, and handle Power Platform apps and chatbots with out leaving Microsoft Teams. The built-in low code knowledge platform supplies relational knowledge storage, wealthy knowledge sorts, enterprise grade governance, and one-click deployment. Dataflex is meant to floor key enterprise knowledge for constructing low-code apps that tackle enterprise issues. The relational database additionally brings AI, efficiency, and safety advantages out-of-the-box.

Microsoft’s Power Platform is a enterprise software that lets anybody analyze, act, and automate throughout their group. Microsoft Teams is the corporate’s Office 365 chat-based collaboration software that competes with Slack, Facebook’s Workplace, Google Chat, and even Zoom.  Since 2018, Microsoft Teams has been the corporate’s fastest-growing enterprise app ever, lengthy earlier than lockdowns began juicing up distant work and studying numbers. In April, Teams hit 75 million each day lively customers, and in May Microsoft’s Jeff Teper instructed VentureBeat Teams “will be even bigger than Windows.”

At its Build 2020 builders convention in May, Microsoft gave enterprise builders new instruments to construct Teams apps. At its Inspire 2020 companions convention this week, Microsoft is doubling down on serving to companies transition to a hybrid distant work method.

“What we’re seeing is that people want to get work done and want to go integrate with business processes in the collaboration environment they’re using each and every day,” Microsoft CVP Charles Lamanna instructed VentureBeat. “What that means is ‘How can I have chatbots interact with me inside of Teams?’ or ‘How can I have an application experience run a business process that connects to my line of business systems right inside of Teams?’ or ‘How can I get access to visualizations and reports around data, like for sales reports or end user satisfaction?’”

Dataflex and Dataflex Pro

Dataflex in Teams means enterprise customers can retailer and handle enterprise knowledge with the Power Platform. In the previous, there wasn’t any supported place to place the information.

“Right inside of your existing Teams and Office license, you can now build apps and chatbots and reports and things like that on top of your business data,” Lamanna stated. “The Dataflex component is really important because at the heart of almost all of these applications and bots that people want to go create is a need to go store and manage all of your different business data in a secure way, while at the same time making it be open and sharing so you’re not creating data over and over again.”

Microsoft Teams event itinerary

Dataflex is constructed atop the Common Data Service, which was once a part of the Power Platform however is now instantly built-in into Teams. It hit common availability 4 years in the past and has since launched assist for Dynamics 365 and Power Apps. Common Data Service has now been renamed to Microsoft Dataflex Pro. “Dataflex Pro is the same data platform, but there are some additional premium features, which power the Dynamics 365 products, as well as the premium Power Apps licenses,” Lamanna defined.

Dataflex means there isn’t any want to connect with storage — anybody can create customized knowledge tables which are team- and scenario-specific. There’s an setting for every crew, with no restrict on the variety of apps — the concept is that a number of apps share your knowledge in Dataflex. If your corporation handles monitoring points, inspections, and repairs, for instance, all these apps use the identical grasp record of belongings.

Built-in AI capabilities

Because Dataflex is constructed on the Power Platform, you additionally get entry to synthetic intelligence and predictive capabilities. Power Automate’s AI Builder enables you to parse structured and unstructured knowledge from paper-based invoices, pictures, and different analog sources. There are six situations from AI Builder that work with Dataflex: class classification, entity extraction, key phrase extraction, language detection, sentiment evaluation, and prediction. Lamanna elaborated on the final one.

“AI Builder provides a low-code experience for using artificial intelligence and machine learning,” he stated. “It supports scenarios — like you can go look at a table in Dataflex and say ‘I want you to predict this column for a row whenever it’s inserted.’ And you can use that to project the likelihood that an expense report will be rejected or not, based on historical data. And you can do all of this without having to be a data scientist. You don’t have to know Python or any of that. You just do it via programming by example or machine teaching. You provide the sample data, which you already are storing in Dataflex. You say what field you want to predict and we’ll just be able to predict the future records that are added.”

Security and Performance advantages

Today, the Power Platform helps over 350 knowledge connectors. They enable enterprise customers to connect with different enterprise methods (an SQL server, an Excel file, a SharePoint record, or on OneDrive or Dropbox) to retailer their knowledge for his or her app or chatbot. Instead of configuring that different system to retailer this knowledge, which provides friction and complicates safety, Dataflex places all of it collectively.

Microsoft Teams Power Virtual Agents

That’s a win for safety, for the reason that knowledge is not saved individually. “Having it all in one allows you to easily share the app and the data as one unit, and it also makes sure that you have really great product integration because it’s all one stack,” Lamanna stated. “This ensures that your security model for your app stays with your data. Whereas if you use a connector, there’s a security model for your data and a security model for your app, which can cause weird stuff to happen exactly as you described.”

There are additionally efficiency advantages. “The connectors today all work via basically virtualization and direct connectivity. So there’s not data freshness latency, but there is a performance impact as you are calling out to another system. There are performance benefits. Security is easier to manage. Your app and your data can be wed together much more naturally.”

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