What Are Data Applications? Moving from Data Rich to Information Rich

Big data has taken over the world. Once upon a time, terabytes were a useful measure of volume for the world's data. Now that volume has stretched to petabytes and even zettabytes, much of which exists outside company research and transaction systems. 

In fact, in the time it takes you to read a few paragraphs in this article, over 50 hours of video will have been uploaded to YouTube, millions of searches will be launched on search engines, and millions of dollars will be transacted via e-commerce. The increase in big data isn't limited to just tech companies. This great flood of data is impacting nearly every industry. 

It's long been known that there are many big data applications, such as more personalized marketing or predictive inventory ordering, but most businesses haven't been able to organize their big data in a way that's useful.  

But what exactly is big data? It's a phenomenon where more information is being generated than can be processed with your current data management systems. Or, in other words, it's when your company is data rich but information poor.

Having large stockpiles of data can be game-changing when it's being used to generate breakthrough insights that inform smart business decisions. However, without the tools to interpret that data, you're left with an overwhelmingly large database that’s just waiting to be utilized. 

The solution to big data is a new concept: data applications. 

What exactly are data applications and how do they work?

Data applications, as a concept, are still relatively new. There isn’t even an agreed-upon definition for them yet. And all apps could technically be called data-driven applications because they require data to function. 

However, in the business intelligence and analytics world, data applications are characterized by a graphical user interface (GUI) that reveals the resources that are available in databases to users. It enables users like business analysts to run custom queries to a database to help them make more informed decisions. 

Put more simply, data applications (not to be confused with database applications) are a mix between data visualizations and web applications in that they allow end users (decision-makers, subject matter experts, and even consumers) to visualize and effectively manipulate large sets of data.

Travel booking websites are a good example. Sites like Orbitz and Kayak deal with a significant amount of data that has to be moved around and visualized in an interactive way so it’s easy for consumers to find a flight they want and book it. 

Imagine if you used these sites and were only able to look at the flight information and then had to call a travel agent to actually book the flight for you. That would be a lot more work and not very convenient. 

But, this scenario is similar to what many organisations are doing with their own stockpiles of big data. The data application movement is about transitioning from an environment where end users merely look and report on data to an environment where anyone can easily visualize, interact with, and interpret big data as part of their everyday work.

Examples of data applications 

Here are a few examples of data applications:

• Orbitz: Technically, Orbitz is a travel fare aggregator website that includes a metasearch engine. Its operations run on a mixed Red Hat Linux- and Solaris-based platform, and it uses a clustered Java environment. Orbitz works with brands from around the world so it has to be able to accurately distribute information from multiple countries, companies, and currencies, all while delivering a consistent and stable experience for end users across the globe. 
• Exaptive: The mission of this software development company is to drive innovation by connecting data, tools, and people so that productive and creative collaboration becomes a more normal occurrence. Customers include healthcare organisations, which are using the data management application to help find hidden resources in public health data, avoid redundancies, and accelerate knowledge sharing in epidemiology. 
• Dataiku: This all-in-one data, centralized data platform helps businesses aggregate, visualize, and interact with their big data. Whether businesses use it for analytics at scale or to take advantage of enterprise-level AI, Dataiku's self-service platform helps companies operationalize machine learning so they can easily discover and act on useful insights.

How legacy infrastructures obstruct data applications from empowering businesses

Data applications can offer tremendous benefits for businesses of all kinds. Unfortunately, many organisations are hampered by low data mobility that results from fragmented legacy IT infrastructures, such as data silos. 

For an organisation to take full advantage of the power of its data applications, it will need to have access to all of its data. But because data within legacy IT infrastructures tends to be organized by internal departments, each with their own workflows, lingo, and software, much of the data that’s gathered doesn't easily translate or transfer across the organisation. In short, the siloed nature of legacy IT infrastructure leads to poor data mobility across an organisation. 

Consequences of siloed data storage include:

• Increased costs to manage the complexity of a fragmented data ecosystem
• Inconsistencies, redundancies, and overall lack of synchronization between departmental data
• Limited data mobility between on-premises and cloud infrastructure

If your business intends to effectively utilize big data applications, you'll need to modernise your IT infrastructure and transition to a data management application.

How Pure Storage can help accelerate your data applications

The future of data is big, fast, and consolidated—and Pure Storage has the comprehensive data storage solutions you need to embrace it. 

Named a leader in the 2021 Gartner® Magic Quadrant™ for Primary Storage, Pure offers data storage that is flexible, agile, and easy to manage. 

Benefits of powering your data applications with Pure include:

• Consolidation into a unified data hub that can handle high-throughput data streaming from a variety of sources
• Truly non-disruptive Evergreen™ upgrades with zero downtime and no data migrations
• A simplified data management system that combines cloud economics with on-premises control and efficiency
• Fast and efficient scale-out flash storage with FlashBlade®

With all of your company's data stored in a responsive and easy-to-navigate platform like Pure Storage®, you'll be able to unlock hidden insights and act decisively upon them to achieve your business goals. Whether it's bringing a new product to market, leveling up your data protection, or accelerating your core applications, Pure delivers the performance and scalability needed to meet the demands of modern data.