CIO Influence Interview with Steve Leeper, VP of Product Marketing at Datadobi

Steve Leeper, VP of Product Marketing at Datadobi talks about Datadobi’s newest features, their StorageMAP 7.1 platform, challenges surrounding data management and more in this CIOInfluence Q&A:

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Hi Steve, tell us about yourself and your marketing journey and highlights from your time at Datadobi:

I’m the VP of Product Marketing at Datadobi. I have over 30 years of experience in the IT industry, during which time I held various technical and sales roles at companies including Andersen Consulting, Sun Microsystems, and EMC. At Datadobi, I oversee product marketing development and manage the presales sales engineers team globally.

When I joined Datadobi, we had two successful products focused on unstructured data—one for data migration and one for data protection. In recent years, we have used the core technology developed for those products as the foundation of our data management platform, StorageMAP. This unstructured data management software provides deep insights and actionable intelligence to help organizations manage and derive value from large volumes of unstructured data. It’s just the beginning, but it is an exciting time to be in this market.

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We’d love to hear from you about some of Datadobi’s newest features and how they are a game changer for the industry and end users.

According to an IDC report sponsored by Datadobi, “more than 80% of the data created over the next five years will be unstructured.” The report also notes that “Enterprises should implement a conscious data management strategy to handle the deluge of data.”

However, managing unstructured data is no small feat. It often exists in silos, scattered across various storage devices, cloud environments, and physical locations. Compounding the issue, much of this data may be outdated, unowned, or irrelevant to the business. Such clutter not only undermines compliance efforts but also reduces the overall value and usability of the data.

To address these challenges, we developed StorageMAP—a comprehensive solution designed to provide organizations with detailed insights into their large-scale unstructured data environments. By enabling data analysis and visualization, StorageMAP helps businesses reduce risks, streamline decision-making, and optimize their data management strategies.

For example, high-quality data made accessible through StorageMAP can fuel initiatives like generative AI (GenAI), unlocking the true potential of unstructured data and driving improved business outcomes.

How is your latest StorageMAP 7.1 platform enabling better data protocols for CIOs and IT Decision Makers?

StorageMAP 7.0 introduced more data insight capabilities, customizable dashboards for policy management, a new analysis module to support decision-making, advanced policy-driven data placement features, and cost control and ESG compliance tools. Our most recent version, 7.1, built on these features by offering improved scalability and performance through our Unstructured Data Mobility Engine (uDME), the core of the platform of StorageMAP This latest version includes example dashboards designed to help new customers kickstart their data management journey effectively.

It also has enhanced analysis options allowing customers to analyze data on a wider variety of metadata characteristics. This makes it easier to find the proverbial needles in the haystack when evaluating a large, complex data environment. effectively.

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What are some of the biggest challenges surrounding data management today that businesses and IT teams largely struggle with?

Today’s businesses face significant challenges in managing the sheer volume and complexity of unstructured data. Organizations must juggle multiple data sources from various vendors, oversee hybrid environments, control escalating storage costs, ensure regulatory compliance, and meet sustainability goals—all simultaneously.

Addressing these challenges requires modern data management solutions paired with strategic, organization-wide plans. Only then can businesses achieve efficient, cost-effective, and sustainable data management across their entire ecosystem.

How can businesses use AI effectively here to drive better processes?

Billions of data files equate to an inordinate amount of effort to sift the correct data to train and/or augment large language models (LLMs). LLMs rely on massive datasets to learn patterns, so choosing the correct data is critical for producing accurate, useful, and unbiased results.

Often overlooked is how data stored in the data lake is turned into quality datasets. If you put garbage in, you will get garbage out. Therefore, we can’t overlook this critical first step of data preparation and management.

Much like managing traffic on a busy highway, we must ensure smooth data analysis to prepare it for training GenAI models. If we get the data where it needs to be first, we can achieve the ROI promised by LLMs.

A few unstructured and structured data management practices that you feel should serve as fundamentals in a digital first business ecosystem?

• Data Discovery and Classification: After analyzing your data, you can classify it, ensuring it’s properly organized and accessible.
• Data Mobility and Flexibility: find a data management solution that helps with data migration and integration across different platforms and environments.
• Effective Data Governance: create policies for managing unstructured data, ensuring compliance with regulatory requirements and corporate standards.
• Redundant, Obsolete, and Trivial (ROT) Data Management: routinely identify and eliminate ROT data to optimize storage and improve data quality.
• One Window View: pick a solution that can overlay all of your storage and cloud environment so you can optimize your storage and manage your data needs.

Some thoughts pertaining to the future of data management as IT systems and layers get more complex due to multiple integrations and rising threats?

The future of data management lies in leveraging tools that unlock the true value of your data. With the integration of AI and ML, businesses will be able to proactively and intelligently manage data as it accumulates and ages. Advanced automation will play a pivotal role in keeping pace with the exponential growth of data, ensuring more efficient and streamlined management.

A few insights into Datadobi’s roadmap for 2025 and beyond?

Datadobi follows a structured approach with three major product announcements each year. As StorageMAP continues to evolve, our focus remains on expanding both the depth and scope of the platform.