How building applications on a modern data platform fosters agility, speed, and innovation (VB Live) | VentureBeat

Presented by Snowflake

Software teams have turned to building their applications on modern data platforms, across many use cases and industries. Join this VB Live event to hear from product and engineering leaders about the advantages of the data cloud, the problems they’re solving, key learnings, and more!

Instantaneous access to multiple sources of data, and the ability to connect it to machine learning, has turned every application into a data application. These applications, both customer- and employee-facing, process large volumes of complex and fast-changing data, with analytics capabilities, and the power to give users access to their data within the application.

There are a number of common use cases for data applications. That includes marketing or sales automation that requires a complete view of the customer relationship; IoT devices and sensors; application health and security analytics; machine learning (ML) and data science; and embedded analytics, or branded analysis and visualizations delivered within an app.

How the cloud fosters innovation

Data-intensive applications like these require a modern data architecture to meet customer expectations. Many application builders have migrated to the cloud from legacy data stacks in order to overcome growing pains and harness its scale, speed, and elasticity. The cloud offers real-time access to data, and allows teams to scale instantaneously, even across regions.

Others are building apps on platforms like Snowflake’s, which is specifically designed to address the biggest challenges in building highly performant data applications.

Data platforms can gather, analyze, and process with large amounts of data in near-real or real-time, support a variety of data types and structures, be able to interoperate with external tools and data sources, and scale efficiently to manage the demands of customers without wasting resources. That’s why data applications in the cloud are a game changer for IT teams, because it has become as easy as using a service.

“Developers can go back to innovating, building forward-facing applications or expanding the applications and thinking about the next project they’re working on, because they can set up a new warehouse within a couple of seconds and expand it and scale out that workload as needed,” says Natalie Mead, senior director, field CTO Office, at Snowflake.

Improving the end user experience

Customers and end users can be fickle, Mead says. It’s easy for them to move to another application if it isn’t driving at the speed they need it to, or if they’re not getting the optics they’re looking for. The end users might be shoppers at a grocery store, customers at a restaurant, health care providers, and more, because every industry is developing these data applications.

“But there are 15 other applications in the background ready to go,” she explains. “If you’re not able to, as an entity or a company, give sub-second or very quick access to data through your application, they’re going to move on.”

She points to one of Snowflake’s customers, which has a data application that doctors and patients use, that runs analytics around security and safety procedures. In health care you can’t risk making a mistake, and you need to have access to your data immediately. As an end user, and especially in health care and pharma, if you don’t have the right information, you’re putting people’s lives at risk.

The best way to differentiate your offering is to select the right underlying architecture, because modern data applications that deliver real-time value at massive scale require a modern data platform designed for high-performing customer experiences.

“That’s where we’ve been able to succeed, because we’re driving a bunch of different needs for very different customers,” Mead says. “Someone who might be looking for paper towels, versus someone who’s trying to figure out safety precautions around a new drug release, they have very different needs and we can scale and adjust accordingly. They have so many different nuances to what they’re looking for. We’ve been able to really attack at the speed our customers need and that end users are expecting.”

Breaking down the data silos

Having data in the cloud makes it more accessible to a variety of stakeholders who may not have a lot of expertise in data. You don’t have to be a data scientist or engineer, understand modeling, or how to build training models. Content can be built into basic dashboards that serve data up in any format on the company side, or securely exported for end users into their applications, using data masking to preserve consumer privacy.

The data can even be shared securely between entities, Mead notes, such as the financial services companies and retail companies that want to share customer data with other companies to develop intel on marketplace trends — in order to build out even bigger applications.

“You have companies that all want to work together to find these trends and build out much bigger and more exciting applications,” she says. “They can easily and securely share data between two totally different entities that would never, in a traditional model, share that information, and it’s all secure.”

Embracing change

Mead’s biggest piece of advice, when it comes to turning to the cloud or data application platforms to harness data for applications, is to embrace the rapid change that’s going on.

“Technology changes every hour,” she says. “Be very comfortable and be forward-thinking around the agility you need to move to cloud. You can’t just be set in your ways. There’s something new and exciting all the time, so buckle up.”

You’ll learn best practices to:

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