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January 31, 2019

Data Management Falls Short for Unstructured Data

Allison Armstrong

(Valery Brozhinsky/Shutterstock)

Although data-centric enterprises have adequate strategies in place for managing their structured data, current tools are not sufficient for managing the recent wave of unstructured data growth, according to a new report.

The report, which was commissioned by Igneous and is titled “The State of Unstructured Data Management,” surveyed 200 IT leaders across a broad set of industries, assessing data management challenges and priorities for structured vs unstructured data. The report is in its first year.

This year, the report focused on what’s driving the rapid growth of unstructured data, the pain points that organizations face managing this data, and how IT teams can improve their unstructured data management strategy.

The survey revealed that while unstructured data volumes and  business relevance are on the rise, data-centric organizations are currently struggling to achieve their unstructured data management (UDM) goals.

Unstructured datasets are growing quickly. The typical organization reports its unstructured data growing 23% annually, which means it will double every 40 months. Roughly one-fourth (24%) cite growth rates in excess of 40%, where total unstructured data doubles every 24 months.

“Our data is much more valuable than we’ve ever thought,” says Jeff DiNisco, CTO of P1 Technologies, an IT consultancy based near Los Angeles, California. “That’s why we save so much of it.”

Unstructured data is growing rapidly due to the increase in machine-generated data and machine learning initiatives. Respondents of the survey reported that 55% of their data is generated by machines.

Importantly, organizations highly value and rely on their data, making data management a key business priority.

The typical respondent reports that 40% of their organization’s value comes directly from their data. They rank the value of their data ahead of every other asset they were asked about, with the exception of their customers and employees. That makes data more valuable than their brand, physical assets, and inventory.

One reason that UDM falls short is because managing unstructured data requires different approaches, priorities, and capabilities than the traditional approaches to managing structured data.

The survey asked respondents to list their goals for both structured and unstructured data management, and found that organizations are prioritizing accessibility and insight of unstructured more than structured data. This represents a key difference in how organizations must manage unstructured vs structured data.

IT pros have different priorities for structured data versus unstructured data (Source: Igneous’ “2018 State of Unstructured Data Management Report”)

In addition, respondents ranked “automating data workflows through APIs” as the most difficult UDM goal and “data accessibility” as another difficult and important UDM goal. Neither of these data management aspects were cited as difficult goals for structured data.

When it comes to unstructured data, organizations are faring poorly with two of the four most important data management goals — data insight and data accessibility. In short, organizations are well-equipped to tackle yesterday’s structured data goals of performance, security, capacity management and data protection, yet struggle with today’s unstructured data goals of data insight and accessibility.

The survey results demonstrate that legacy solutions for managing structured data don’t cut it for this new age of unstructured data. Organizations need tools for UDM that help them achieve their goals, including accessibility and insight.

“You can’t just throw hardware at the problem of disk-based data protection,” says George Crump, Chief Steward for Storage Switzerland. “Solving this problem is more difficult than that–it requires process and intelligence.”

For data-centric organizations, failure to manage their unstructured data could be costly and affect their  top line.

“Organizations are struggling to manage their unstructured data. It may be that they can’t handle the current scale or perhaps they can’t handle the file count, but the situation is that most are pretty immature in terms of data management,” P1 Technologies’ DiNisco says.

About the author: Allison Armstrong is vice president of marketing for Igneous. Prior to Igneous, Allison was vice president of  product and technical marketing at Alert Logic. She has successfully led teams and growth strategies in the data protection, IT analytics, cloud security and IT transformation spaces, with companies including Apptio, Quantum and Symantec. 

Related Items:

5 Critical Steps for Identifying the Value in Your Unstructured Information

Taming Unstructured Data with Cognitive Computing

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