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You’ve heard it a thousand times by now. The sheer scale of unstructured data growth, coupled with its dispersion across numerous locations and formats, has created a complex array of silos. This makes data access exceedingly difficult for technologists and compromises data quality, driving up costs and impeding effective data governance. 

This is especially the case when data is used f or advanced analytics and artificial intelligence (AI) initiatives. Recognizing these challenges, in a continued expansion of our longstanding partnership with IBM, we have announced the integration of Panzura Symphony with IBM Storage Deep Archive®. 

This is a move that shifts the conversation around cold data to a forward-looking discussion around data management and the ability to unlock the full potential of archived information within a data fabric architecture. 

Our collaboration with IBM addresses the critical need for efficient and cost-effective data archiving, particularly for the vast quantities of infrequently accessed, yet perpetually retained data that organizations accumulate. 

Combining Symphony intelligent data handling capabilities with the high-density, economical on-premises storage offered by IBM Storage Deep Archive on the IBM Diamondback® tape library, businesses can streamline their archival processes and significantly reduce their storage expenses, whether in cloud or on-premises environments. 

This integration not only simplifies data migration but also ensures that archived data remains readily accessible for today’s data-hungry applications, especially those powering DevOps, analytics workflows and AI pipelines. 

Metadata-Derived Intelligence Unlocks the Value of Data  

The work undertaken between Panzura and IBM extends beyond this latest integration. IBM has natively incorporated Symphony’s data movement framework into IBM Fusion Data Catalog®, creating a highly scalable data fabric that accelerates metadata tagging and provides an enriched business context for data insights and actionable intelligence. 

This integration facilitates comprehensive content scanning, enabling organizations to pinpoint sensitive data such as Personally Identifiable Information (PII). Notably, Symphony is the sole third-party solution embedded within IBM’s Data Catalog software ecosystem, a testament to its unique value in IBM’s data vision. 

The initial benefit of Symphony integration with Deep Archive lies in its ability to expedite and simplify data mobility within a broader data fabric. Symphony acts as a central control point, orchestrating the movement of data to Deep Archive with precision and efficiency. 

Imagine the seamless transfer of vast archives of medical imaging data, financial records, or seismic survey results to a secure, cost-effective and low carbon footprint repository. This streamlined process is vital for organizations facing stringent regulatory compliance mandates, ESG targets or those needing to free up expensive primary storage. 

Symphony’s ‘single pane of glass’ interface and automation capabilities make it an ideal starting point for technologists and data teams seeking to modernize their data management practices. This allows them to align seamlessly with the focus on data fabric automation to improve productivity, reduce cost, and enable governance and compliance. 

Its ease of use also lowers the barrier to entry, allowing teams to quickly realize the benefits of efficient data movement. This strategy demonstrates Symphony’s value proposition, paving the way for broader adoption of its comprehensive data services within the context of a unified data fabric. 

That’s where teams realize the broader implications. It’s like a light bulb turning on. When technologists understand the value of Symphony for data movement, they naturally begin to exploit its metadata support to elevate the archival process to a new level of sophistication within a data fabric. Before data reaches Deep Archive, datasets are meticulously classified and tagged, creating a comprehensive, searchable catalog. 

This achieves the core data management goal – which is also at the heart of IBM’s data fabric vision – of capturing all possible metadata across operational sources, data lakes, and data warehouses. This catalog, accessible via user interface, APIs and JDBC, empowers users to locate specific files without retrieving entire datasets. 

With support for over 500 data types and automatic extraction of embedded metadata, the solution provides unparalleled visibility into archived information, a crucial component for a successful data fabric. 

Metadata-driven capabilities, moreover, enable intelligent policy automation, such as automated recall and deletion, ensuring optimal storage utilization and compliance. Leveraging metadata to identify and relocate cold data, for example, organizations can minimize storage costs and maximize the value of their archived assets, all while contributing to the overall effectiveness of the data fabric itself. 

AI-Powered Insights and the Future of Data Management 

The power of this integration lies in its ability to unlock the potential of archived data for AI retrieval augmented generation (RAG) pipeline and machine learning (ML) workflows within virtually any file or object store data ecosystem. In industries like life sciences, financial services, and energy, where vast datasets are crucial for training and deploying AI models, the ability to seamlessly access archived information is paramount. 

Unfortunately, poor data quality and consistency negatively impacts trust in data. As an IBM survey of Fortune 500 companies revealed, fully 80% of business executives surveyed do not trust their data. Furthermore, multiple locations, clouds, applications, and data silos hinder timely delivery of the right data to the right users, with only 45% of enterprise data that is useful for analysis being analyzed or fed into AI. 

Finally, lack of a consistent understanding of data across an organization can hinder data utilization, with 26% of the survey respondents citing expanding companywide data literacy as a high or critical priority. Symphony, as a part of IBM’s emerging data fabric, addresses these issues. 

IBM Deep Archive, leveraging tape technology, provides an air-gapped, encrypted storage environment, safeguarding data from cyber threats while maintaining accessibility for AI applications, via Symphony. Furthermore, Deep Archive offers significant cost optimization, reducing storage expenses by up to 83% compared to other service providers, and importantly, with zero recall fees. 

Panzura Symphony complements Deep Archive by automating data lifecycle management and enabling smooth data transfers within the data fabric. The integration utilizes S3 Glacier Flexible Retrieval storage classes to fully automate data movement to tape, simplifying archival workflows. IBM Deep Archive on the Diamondback tape library offers up to 27 PB of storage capacity and up to 16.1 TB per hour performance within a single rack footprint. 

This solution offers several key advantages. IBM Deep Archive’s compact, high-density storage significantly reduces energy consumption, aligning with sustainability goals. The combination, as well, of Symphony’s data governance features and Deep Archive’s air-gapped, encrypted storage provides a comprehensive data protection strategy. 

The integrated solution minimizes storage costs and, ultimately, it facilitates seamless access to archived data for AI and ML pipelines, enabling data-driven insights and innovation. And finally, automated data transfers and unified visibility streamline data management, reducing operational overhead. 

Symphony is a part of IBM’s emerging data fabric, offering significant performance and cost management opportunities at the workload element level. Applying a data fabric architecture, technologists can finally democratize access to data and AI, joining them together to focus on multiple workload ecosystems. 

This integration, while at its core is an archival storage changemaker, is not just about archiving. It’s about making data ready for high-value analytics and AI, enabling a new approach through a robust and efficient data fabric. 

The combined power of Panzura Symphony and IBM Deep Archive signifies an advancement in data management, addressing the escalating challenges of data growth and complexity while paving the way for AI-driven innovation and real business value.