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Careers Video. Social media. Chat bots. Websites. Slide decks. Video conferencing. All unstructured data. All a potentially major headache for an industry like yours that must store hundreds to thousands of terabytes of it.
If it’s not organized, catalogued, and tagged in a database or spreadsheet, it’s a problem. And that problem is not going away anytime soon: IDC projects that 80% of data will be unstructured by 2025.
Why is it a problem? A) Because you’re paying to store all this data, but may not be fully capitalizing on its value. And B) this data is central to the way we communicate today—and only by analyzing unstructured data are you truly able to come up with the best possible insights.
Buried within all of this uncategorized information is a potential revolution for how enterprises across industries create products, optimize expenses, and provide better service to customers.
Let’s dive into a few examples of unstructured data applications, considerations for how you can handle your organization’s unstructured data, and, finally, how the hybrid cloud may be a viable solution for storing and organizing it.
Examples of unstructured data applications
Unstructured data can provide actionable insights across a multitude of industries and use cases. Among them:
Example 1: Marketing
Key marketing initiatives, such as monitoring brand perception, rely on unstructured formats: How is your brand talked about across various social channels and platforms? How do you get detailed information from the audio captured during customer calls?
Example 2: Autonomous driving
In autonomous driving, massive amounts of data are created. Today’s autonomous test vehicles typically generate 5TB and 20TB of data per day, which will only grow as system sophistication increases. That’s a lot of data, and guess what? It’s almost all unstructured.
Example 3: Financial services
When we take a look at financial services, it’s the same story. Customer communications in audio files, documents, and audit reports can identify trends that can be leveraged for better product offerings and improved customer experiences. Banks can also benefit from automated compliance reporting, better risk evaluation, and personally tailored wealth management.
Example 4: Internet of Things (IoT)
IoT, with its endless edge devices and sensors, is exacerbating the problem. Look at the Fitbit on your arm, continuously sending your health data to some repository. Your car has 6 or 12 cameras and a thousand sensors in it, all recording your every turn. Even your refrigerator monitors what you’re eating. So, while we see unstructured data exploding everywhere, the speed and volume at which it’s generated really lies in machine-generated data.
With all this data being generated, and at an increasing rate, it’s imperative that your organization has a plan for how best to manage it and use it all.
Considerations for your unstructured data
The first step to handling unstructured data is to understand how complicated it can be and what it requires. Think of this as the three Vs:
Volume
As we’ve said, unstructured data is growing in leaps and bounds. And artificial intelligence (AI) and machine learning (ML) increasingly require the most data possible for training. When it comes to data analysis, more is more.
Velocity
To complicate matters, velocity is becoming critically important. This is especially true as enterprises require more data to be processed in real-time for timely, actionable insights.
Variety
Finally, the variety of data must also be accounted for. For instance, social data behaves in unique ways and requires minimal storage. Meanwhile, video and imaging are completely different and require massive storage models.
While the three Vs present challenges, it is critical for businesses to leverage as much data as they can. And with all the attention the cloud is receiving, it’s tempting to think that the cloud has all the answers.
However, you need to consider that the cloud is really optimized for specific uses of data, and storage of massive, unstructured quantities of it may not make sense for some organizations. There are many instances in which on-premises infrastructure offers multiple advantages, not the least of which includes knowing exactly where your data is located. Other key benefits include things like savings on long-term storage and eliminating costly and time-intensive movement of data to and from the cloud.
The good news is that there’s a way to get the best of both worlds.
The hybrid cloud solution
Hybrid cloud offers the advantages of an on-premises datacenter, including the ability to effectively store unstructured data, while still leveraging the compute and workload scalability of the cloud. This makes it accessible for analytics, while maintaining on-premises governance and security controls.
A hybrid cloud solution often means additional significant cost savings since you employ the infrastructure you’ve already invested in, and your teams can keep working with both the on-premises and cloud-based tools they’re familiar with.
Some specific examples of hybrid cloud usage include:
- On-premises data lakes with governance and security protocols to democratize data
- Cloud hosting of specific workloads and applications that use specific and controlled sets of data—structured and unstructured
- Monitoring and reporting tools to provide visibility into cloud workloads
- Ongoing cloud cost monitoring to avoid runaway cloud expenditures
Getting started with unstructured data
Redapt can help you start utilizing unstructured data today. And our collaborative strategies with Dell EMC mean you can scale as much as you need to, while enabling easy data mobility to and from the public cloud.
Unstructured data is growing. Your insights should be too.
If you’re interested in exploring unstructured data solutions for your company, reach out to Redapt to get started today.
Not ready to move forward quite yet? Click here to check out our in-depth guide to managing and scaling your unstructured data in a hybrid cloud
Otherwise, click here to download our FREE guide to Managing and Scaling Your Unstructured Data in a Hybrid Cloud. You'll learn how you can put unstructured data to work effectively by using it on-premises and in the cloud.
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