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Komprise, a leader in analytics-driven unstructured data management and mobility, today announced the latest version of Komprise Intelligent Data Management, building upon its Komprise Smart Data Workflows portfolio of solutions.
Komprise assures that the new solution can cut business storage, backup and cloud costs by 70% while making data easily available to cloud-based data lakes and analytics tools. TechRepublic spoke to Krishna Subramanian, co-founder, president and COO of Komprise, to get an inside scoop on its latest tools and why unstructured data management is critical.
SEE: Checklist: Cloud storage management (TechRepublic Premium)
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The big picture for unstructured data
“Enterprise IT organizations are struggling to control the rampant growth of unstructured data, such as documents, video and audio files, applications, research and sensor data,” Subramanian said. “They need automated ways to manage the costs of storage, backup and cloud, and they need to make it easy to extract business value from the data.”
Komprise’s 2022 State of Unstructured Data Management Report reveals that global data volumes will reach 97 zettabytes in 2022, more than double the total data production before 2020. The exponential increase in data is linked to digital and cloud transformation and acceleration.
Most of this data is unstructured, requiring additional efforts to clean, manage, migrate, store and prepare for use. This is amplifying pressures on enterprise IT: More than 50% of enterprises are managing at least 5 petabytes of data today, a percentage that has grown significantly in just one year.
The big question is what to do with all of this data. Doing nothing or choosing the wrong strategy can devastate companies. Impacts can range from data waste errors to significant revenue losses and cybersecurity risks. Leveraging unstructured data is also proving to be critical for facing economic slowdowns, navigating regional tensions and disruptions, and keeping up with the evolving legal data landscape.
Intelligent Data Management offers new solutions for unstructured data
In addition to the aforementioned problems with unstructured data management, companies complain that creating reports for users takes time and doesn’t always give people the answers they need. Subramanian explains that IT organizations “are spread pretty thin.”
“Our customers tell us they want to find ways to give departmental users secure self-service capabilities,” Subramanian said.
With its expanding unstructured data management tool set, Komprise is offering customers a possible solution. Komprise Intelligent Data Management allows central IT to authorize departmental end users to interactively monitor usage metrics and data trends, tag and search data, and identify datasets for analytics.
These new Komprise features solve IT’s storage infrastructure cost problems while allowing users to find and operate the right datasets.
“Our latest release is focused on providing secure, delegated self-service, which helps data owners or managers—usually in IT or data science or research roles—participate in decisions regarding how their data is handled,” Subramanian said.
Komprise solutions can also help IT organizations manage costs, a benefit that is in great demand due to the global economic landscape.
SEE: Storage for unstructured big data should be part of a company’s strategy (TechRepublic)
Komprise Intelligent Data Management capabilities
From visualization to the integration of data governance and data quality policies, Komprise’s new smart solutions automate and simplify the entire lifecycle of unstructured data management. With Intelligent Data Management’s latest tool release, customers can expect the following features.
Visualization and access
In an interactive dashboard, authorized departmental users can monitor and understand their data usage. More specifically, they can learn how many and what type of files there are, where files are stored, and which files and applications are the biggest consumers of enterprise data resources.
Real-time analysis
Users can create queries to get real-time visibility and manage costs rather than needing to ask IT to create static reports.
User-driven tagging
Users can enrich data with additional metadata tags to facilitate search and data management actions. Use cases for this feature include archival storage or compliance and legal hold.
User-driven tiering and data mobility
Authorized users can identify datasets with specific characteristics to move to cloud storage or other secondary storage. This allows for more cost-effective data management or research initiatives.
Data deletion
IT can set up data movement and deletion as a workflow. The entire process is fully automated. As an example, all marketing campaign files can be moved to archival storage 30 days after project completion and then confined for deletion after two years.
The Komprise data management portfolio
Komprise architecture also ensures users have an efficient and transparent experience when accessing their data, no matter where it has been moved. It transfers data in a way that can be leveraged directly in the cloud or other third-party tools for artificial intelligence and machine learning processing.
Komprise offers the following products and features beyond the Intelligent Data Management platform to support unstructured data management needs.
The Global File Index
This solution provides an easy way to visualize all data and search for specific files across all storage. The Global File Index is compatible with on-premises, edge and cloud file storage formats.
Komprise Transparent Move Technology
Komprise TMT moves data without user disruption; data files are fully accessible from the source, using industry-standard symbolic (sym) links. Komprise supports cloud-native access to data once it is moved to object storage, so users can leverage cloud-native tools for ML and business intelligence.
Elastic Data Migration
Komprise’s Elastic Data Migration reportedly moves data to the cloud 27 times faster than standard migration tools. Customer reviews also highlight this tool’s high level of reliability.
Smart Data Workflows
Smart Data Workflows is a feature that gives IT users the means to create automated workflows for data operations. Workflows can be used to find the right data across storage assets, tag and enrich the data, and send it to external tools for analysis.
Why leaders focus on unstructured data management
Komprise’s survey reveals that 87% of IT leaders rated managing unstructured data growth as a top priority for 2022, a number that went up from 70% in 2021. Leaders say the challenges for this year are “data cloud migration without disrupting users and applications” and high data storage and backup costs. Other primary concerns are visibility, data governance application, and compliance with laws and regulations.
SEE: 5 ways to improve the governance of unstructured data (TechRepublic)
“The recent survey that our company conducted showed that nearly 68% of enterprises are spending more than 30% of the IT budgets on data storage, backups and disaster recovery,” Subramanian revealed. “Storage IT pros need to work with users to make smart decisions about their unstructured data, which is consuming so much spend.”
Valuable unstructured data use cases
The value of unstructured data becomes clear as we examine different examples of how unstructured data is being generated today. In manufacturing, smart factories, the automobile sector, and healthcare and pharmaceuticals, unstructured data is being generated at a rapid pace by the Internet of Things, research and development departments, robotics, smart devices, and endpoints. The value and potential of this data are immense and critical for efficient operations.
In business, finance, banking, capital markets and insurance, companies face the challenge of managing an increased amount of unstructured data from digital financial transactions, customers, markets and business documents.
Managing various types of unstructured data is proving to be complex, but most companies believe the effort is well worth it. Especially when you consider the amount of unstructured data that is generated by social media, surveys, publications and websites, brands are realizing they have the potential to impact brand and customer experiences, marketing, virtual sales and campaigns if they leverage this data effectively.
Using Komprise solutions to optimize your business’s unstructured data
Komprise designed its latest Intelligent Data Management offerings to help IT collaborate more effectively with legal, finance and mergers and acquisitions groups for compliance, all while offering users more self-service data management opportunities. Users need to interactively understand how their data is growing and being used, as well as how to run queries to find and tag data, regardless of whether the data is in the cloud or in a data center. Tools like what Komprise is offering help users meet these new expectations.
“It’s all about giving greater visibility for departmental users on data they own,” Subramanian said.
With Komprise, departments can interactively drill into their own data usage and costs.
“For the first time, departmental IT heads or other data owners can answer questions about their data to support initiatives related to research, analysis, compliance and regulatory audits,” Subramanian said.
Establishing data management best practices that support innovative tooling
Regardless of what tools you select to help you manage enterprise data, you will ultimately fail if your organization does not have the right people and processes in place to support these tools. Companies are increasingly leaning into data literacy training and standardized data governance policies and procedures to ensure the success of these data management tools.
So, if your organization is just now realizing it has a data management or governance problem, start by hiring the right people and setting them up for success with the right documentation and procedures. A resource like TechRepublic Premium’s Data governance checklist for your organization may make the difference between a data management tool and team that sits idle and a dynamic team and tool portfolio that optimizes structured and unstructured data use cases.
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