Typography

Distributed system architectures, including Cloud and big data are changing how network data in organizations is viewed. Network-generated data analysis is increasingly gaining momentum with service providers for network detection and response (NDR) as well as improving the overall quality of customer experience by gaining insight of the network activities and acting upon the flaws.

Detecting glitches in complex IT infrastructure remains a challenge in network analysis as network engineers scratch their heads as they try to keep their networks running optimally in the face of heavy competition in the market. Several network analysis methods such as netflow or other flow-based methods and packet data are explored for troubleshooting and protecting networks. For instance, Network captures or packet captures (PCAPs) are full-fidelity data streams of connection and payload information details. However, the PCAPs data are normally large and difficult to tackle and are better suited for highly targeted scenarios. However, the insight provided by metadata is considered a golden standard when it comes to extracting a clear picture about the health of organizational networks.

What is network metadata?

Network metadata is a record of all communications that happen within the existing network infrastructure (switches, routers, firewalls, packet brokers, etc.), providing granular details of network communications. Network metadata is scalable and can enable whole network monitoring as packet data is collected by an analyzer, sorted, parsed, indexed for a long term with graphs and statistics about network traffic, usage, bandwidth, and even application performance. Metadata is essentially information about data both technical metadata and business metadata. Most security agencies also rely on the metadata insights for developing these security solutions as the data can be leveraged to find, validate and remediate threats faster.

Threat hunting: Break into networks has become a common phenomenon in today’s digital age and data protection is a constant challenge. Metadata provides insights and analytics that can transform the way critical security threats are investigated and understood. Network engineers utilize proactive approaches such as network threat hunting to detect threats by assuming that the network is under attack and malicious activity has already breached traditional security systems such as firewalls, IPS, IDS, end-point protection, etc and finding out the details so the threat can be stopped in the future.  Metadata holds crucial descriptors of the data to create a directory that can be investigated in real-time at a lower cost than a full packet capture system. In short, metadata analysis can reveal the past and present movement on a network that will help in securing the future even from zero-day exploits.

Monetising innovative solutions: The development of urban living and smart cities depends on the power of data and its usage. Today, the data source resides in the cloud environment, IoT sensors, metadata from enterprises or consumers for analysis of behavioural patterns and activities. Under a fundamental privacy framework that enhances consumer trust, telcos can now seek consent from users to use metadata such as location to offer new services to advertisers, transport companies, and local authorities.

Network automation: The rapid increase of network traffic has made manual management redundant. By incorporating AI and machine learning, metadata can be used for automation of the networks whereby software-enabled deployment, configuration, orchestration, testing can be put in place, thus eliminating manual intervention. Additionally, with the adoption of AI and machine learning, metadata can provide new services such as data analytics as a service, dashboard as a service, Cloud Services, blockchain, IoT use cases. Through the combination of metadata insights,  AI, machine learning, and automation, telcos can bring about agility and efficiency along with improved security for low-cost network operations capable of supporting the demanding business requirement of today’s data-driven marketplace.

As CSPs brace to turn into digital service providers (DSPs) who can provide automated on-demand services based upon specific customer requests rather than just connectivity, having a network and service management processes that are intuitive, reliable, and efficient is not an option anymore.

The future lies in creating metadata insights that simplify the analysis of databases and add business logic into next-generation networks. Experts have already predicted that companies that invest efficiently to manage data as a strategic asset will stand a greater chance of success in today’s competitive global economy.

The criticality of metadata management in data management has not been fully realized by many in the marketplace. Whether it is data governance or data quality or data-driven business decisions, metadata can accurately present the data movement process from where they reside and flows across an organization’s multivendor BI systems. A robust metadata management strategy will help organizations bypass incorrect decision-making and save critical investment and time.

Tapping into this network visibility activity, Ericsson recently launched its Network Data Analytics Function (NWDAF) solution, based on smarter data-driven networks that learn and improve. Ericsson’s NWDAF enables service providers to improve customer experience by using the data generated by the network to flag and fix problems, thus improving the service quality.  Ericsson’s NWDAF enables automated closed loops and assurance based on 3GPP and custom analytics use cases and enables multi-vendor interoperability.

The metadata management tools market size is projected to grow from $6.3 billion in 2021 to $15.1 billion in 2026, at a CAGR of 19.0% during the forecast period.

However, organizations must be wary of vendors who are providing metadata management frameworks as different organizations in different industries may require different tools, solutions, and vendors for the purpose. Picking the right vendors after a thorough evaluation of their solutions could make all difference in the organization’s business outcomes.

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