Structured vs. unstructured data: What companies need to know

Most modern innovations and services - those that improve the human condition and create a better world for us and our children - are digital. They start, evolve and end with raw data. Gene mapping has been used for vaccine creation, and mapped gene data is stored in unstructured files. Personal movies from cell phones and security footage from cameras are increasingly recorded in high 8K quality, the same quality as the latest blockbuster movie releases. And these video files are stored in an unstructured file format. Data sets used to train machines to do everything from drive a car automatically to determine the right place to drill for oil use massive amounts of unstructured data as part of their training sets. Everywhere you look, unstructured data is driving innovation.

If managed well and then transformed, this is the case unstructured data can be critical in shaping our modern world. But most modern data technologies were not designed to leverage it. Unstructured data is not only profoundly underutilized, it also faces numerous challenges. But the modern companies that excel at it are not only innovating and creating amazing things to improve our lives, they are saving money and time in the process.

We live in a time when there has never been more data.

Not all data is created equal

When people think of data, they usually think of structured data. But in reality, customers, clients and citizens generate far more unstructured data.

Both structured and unstructured data are invaluable, but they are decidedly different. According to Fintech Futures, unstructured data makes up about 80% of databases. This includes data stored as audio, video and email files, all of which are unstructured data files. Yet when it comes to unlocking the value of unstructured data, "very few companies are leveraging the information they collect," said Ryan Stewart, writing for Fintech Futures. "The biggest obstacle for the banking sector is its extensive and outdated IT infrastructure, with 92% of the world's 100 largest banks still relying on legacy systems."

Structured data vs. unstructured data

Structured data is clean, neat and relatively easy to analyze. It can be easily stored in rows, columns, tables, spreadsheets and databases. Almost all data technology has been developed in the last 10 years to manage and manipulate it. Unstructured data is its eccentric and unruly cousin.

Unstructured Data This is a native file format, also known as file data, and comprises 80% of all enterprise data. It includes image, audio, text and video files - think emails, podcasts, social media posts, presentations, movies, medical imaging, genomics and more. Although unstructured data rarely fits neatly into standard boxes, it is the substance of global change, innovation, collaboration and transformation. And most of the opportunities and possibilities with data lie in unstructured data. It's time to pay attention.

Unstructured data drives innovation and transformation

Unstructured data is on the rise across all industries. According to leading analyst firms, by 2024, organizations will triple unstructured data stored locally, at the edge of the network or in the cloud. And in the wake of a global pandemic - as remote work has become commonplace - the cloud is no longer optional. Rather, it's essential for competitive advantage.

Unstructured data is accelerating digital transformation. But to make new drugs, treat diseases, entertain ourselves, and develop smart machines that enable us to work faster, smarter, and more sustainably, we must not only collect unstructured data, but also transform it into something useful and beneficial.

Dayton Children's Hospital, for example, uses unstructured data to improve patient outcomes and save lives. Physicians at this world-class teaching hospital rely on rapid retrieval and secure archiving of high-resolution medical images for diagnoses and treatments in their world-class pediatric trauma center.

Hyundai-MOBIS, one of the world's largest suppliers of auto parts and components, uses vast unstructured data sets to develop training scenarios for its autonomous driving and connected car technology. This South Korean company stores and analyzes hundreds of terabytes of video data to make vehicles smarter.

Industrial Brothers, a full-service animation studio that didn't have a cloud presence or support remote work before March 2020, uses unstructured data to create, produce and collaborate on children's shows. When their headquarters had to close in response to COVID-19, they, like many other organizations, had to make a quick turnaround. They virtualized their collaborative studio experience and migrated all of their creative and production workloads to the cloud.

These are just three of the myriad companies doing great things with unstructured data. They are using it to gain insights, improve business practices, inform decision making and drive innovation. However, unstructured data must be well managed and easily accessible to do this kind of work.

The use and management of unstructured data is still in its infancy. And as countless other organizations that manage and store data with legacy systems have found, data transformation is easier said than done.

Why unstructured data is a big problem

There's no doubt about it, unstructured data is full of possibilities. But for many organizations, it can be or become a big problem. Here are seven of the most common reasons.

1. organizations struggle to keep up with, manage and access enough storage.

Raw data-often captured by sensors, cameras, sequencers, cars, or other machines-is of little importance until it is learned from and then transformed. This transformation of data into insights for innovation often requires collaboration across massive data sets. And data innovation requires data accessibility. Companies often accumulate hundreds of terabytes or even a petabyte of data that they need to store indefinitely. That's the storage equivalent of 1000 laptops! As the amount of data grows, so must the storage space. Tons of data require tons of storage.

2. Legacy systems were not designed for modern workloads or the cloud.

The old guard of scale-out and scale-up solutions were not designed to handle today's applications, file types, workloads and volumes. And of the two main methods for storing and managing unstructured data - object and file storage - only file systems are designed to handle data in its native file format. Legacy and object storage systems cannot provide the performance, visibility, portability, control or scalability that modern data management and cloud migration require.

3. legacy architecture limits scalability.

Legacy architectures are often local and hardware-bound. Storage is therefore subject to the size of a data center architecture. As computing power scales, storage must scale as well. But data center real estate is expensive. These limitations can stifle creativity and exploration of new ways to create with unstructured data.

4. Data silos prevent access and collaboration.

To address scalability issues, some organizations have turned to storage arrays or multiple data centers. While these solutions temporarily fix storage problems, data silos and disparate storage arrays make real-time access and collaboration difficult. To optimize and harness data insights, consolidated data is ideal.

5. Consolidated data limits storage options.

Unfortunately, consolidated data also has limitations. It requires a bucket large enough to hold it, as well as a size sufficient for many users to transform it. Neither data centers nor public clouds offer more than a handful of storage options - and those limited options aren't great ones. An investment in custom data center hardware requires ongoing investment in custom hardware. And if you're locked into a data center, you're locked out of the cloud unless you move to a hybrid cloud environment. Public cloud options that limit you to a specific cloud also limit your computing power, network and workflows.

6. competitors migrate to the cloud.

By 2022, leading analysts predict that public cloud services will be essential for 90% of data and analytics innovation. And forward-thinking companies - and competitors - know this. They're moving workflows to the public cloud. And unstructured data is only accelerating that migration. The faster companies get to the public cloud, the more competitive advantage they gain.

7. Top talent is moving to modern workplaces that are conducive to remote work and collaboration.

Home workers lack sufficient infrastructure to be productive with big data. They need to go to the office to get their work done. But that won't last long. Top talent will eventually opt for cloud-based workplaces that are conducive to remote work and collaboration.

Do good work with unstructured data.

Managing, storing and transforming unstructured data at scale to drive innovation may seem daunting. But as we embrace new business models, demand data platforms that provide real-time freedom, control and visibility, and simplify the way we manage and store data, it's both doable and possible.

Like other modern innovators, you can use unstructured data to do good work in the world. As you consider and rethink your own unstructured data and infrastructure strategies, here are some suggestions.

1. Be humble about the future.

The cloud wasn't a mandate three years ago, and now it is. When it became non-negotiable, we all said everything had to go to the cloud, but the options were limited. Today, with AWS, Azure and Google Cloud Platform, there are many options, and choice has become a consideration. But what works today may not tomorrow. So look at the future with some humility when making decisions. Select infrastructure strategies that offer future flexibility.

2. Be aware of what you are getting into.

Be laser-focused and selective while sticking to your strategies. Access applications that add value to your end users. Opt for infrastructure software that lets you standardize practices and reduce complexity. Choose a robust file data platform that handles unstructured data in its native file format. Opt for flexible, cost-effective storage that overcomes hardware, data center and cloud limitations. And be skeptical of vendors and platforms with solutions that abuse that flexibility.

3. Be strategic in your move to the cloud.

As you move your business to the cloud, remember this three-step framework: consolidate, extend, transform.

Gather your unstructured data and workloads in one place. This reduces the cost and complexity of managing multiple systems.

Extend your unstructured data and infrastructure to the public cloud. You can do this through cloud bursts or by building individual workloads that can fluctuate between on-premises and the cloud.

Transform workflows to be fully cloud-based. Sustainable digital transformation takes time. So be patient, take strategic steps and be careful not to jump straight to transformation.

Executives who are willing to be humble and intentional about their infrastructure strategies, and who take strategic steps to move to the cloud, can save time and money and retain top talent. With the right data platform, they can gain full control of their data and leverage the value and freedom of unstructured data to drive innovation.