“A modern approach to metadata management will enable information about all data to be consolidated, which allows for a complete view and seamless user experience.“
For businesses to leverage data governance, they need to enforce policy and take action on governance issues before they cause problem
Meera Viswanathan, Lead Product Manager, Fivetran
“Data is the lifeblood of the organisation” is a phrase often repeated when discussing the realities facing businesses in recent years. While one may groan at the triteness of this statement, it makes it no less true. A glance at the numbers highlights why data is worth its weight in gold. India’s online population is expected to increase to 900 million in 2025, according to the Internet and Mobile Association of India.
Official figures say that between 2017-2018 to 2021-2022, the amount of wireless data used by the average consumer in India went from 1.2 gigabytes to 14.1 gigabytes.
Meanwhile, an Ericsson report finds that monthly data consumption is also expected to climb up to 50 gigabytes per smartphone by 2027.
These numbers signal the dynamism of today’s business landscape, and metadata is now critical for organizations to be data-driven. The ability to collect, catalogue, describe, govern access to, and support data discoverability cannot be overstated. However, many businesses lack the tools and an effective strategy to deal with increasing data requests from across the organisation.
While data teams grow and scale infrastructure to respond to these rapidly increasing requests, understanding, controlling and securing what data is entering the system and how that data is being handled can be a challenge.
Decision-makers will quickly find that legacy solutions relying on manual management fall short of this task. Even if at first glance it may appear manageable, the need for continuous manual intervention at every stage of the data’s journey will emphatically prove that the traditional approach is unsustainable.
Empowering access via visibility
Instead of highly inefficient manual maintenance, which can’t deal with surging data volumes and complexity, businesses need automated solutions that help understand the data journey from source to consumption for critical business use cases including root cause analysis, impact analysis and data audits..
The volume of requests for access to data needed for business critical decisions is massive in data-driven organizations. Due to manual processes in enforcing policy and the lack of visibility into the data’s journey upstream of the warehouse or data lake, businesses find they are incapable of providing timely access to data at scale. Data consumers then turn to “rogue” data sources which potentially compromises the quality of business decision – for example, ensuring finance teams are tracking business health using the *right* revenue number!
Remedying this requires enterprise data teams to have full visibility over the data entering their systems (from source to consumption) to ensure access to high quality and trusted data. Data pipelines responsible for moving this data can provide insight into where data came from, who accessed it and what changes have occurred in the pipeline. With this added visibility and context, businesses can also integrate with governance and observability tools, which support data teams – enabling them to understand the context of the data they are accessing and allowing the core data platform team to enforce control over who has access to what data.
Metadata management for modern architectures
For businesses to leverage data governance, they need to enforce policy and take action on governance issues before they cause problems. A manual approach is feasible in smaller organizations. However, as piplines multiply into the thousands, an automated approach that captures data as it moves from source to destination can ensure businesses are equipped to scale access while ensuring compliance without the overhead of manual process.
A modern approach to metadata management will enable information about all data to be consolidated, which allows for a complete view and seamless user experience. As a result, data lineage can be understood from end-to-end, even when passing through multiple systems and tools, boosting trust in the quality and accuracy of data.
Legacy approaches are also incapable of safeguarding data privacy in compliance with the increasingly complex regulatory landscape. While the creases in India’s data protection laws are being ironed out, local businesses still need to be wary of international legislation such as Europe’s GDPR, if they intend to compete with global peers. A modern metadata management approach can help boost compliance through integration into existing privacy and security strategies.
Through centralised governance backed by automation and integration, data policies and
processes can be continually improved. Businesses can then truly leverage their data and translate it into better decision-making, as well as improved performance and compliance.
