By Piyush Agarwal
Ever since the pandemic, the shift to remote modes of working has raised concerns for protecting and managing data effectively. Before the shift to remote working, organizations used to manage their data on-premises, implementing security controls and monitoring all incoming and outgoing traffic, assuming that everything within the organization’s security perimeter was trustworthy. However, with the changing workplace dynamics, employees now have access to office assets and cloud resources through mobile devices from anywhere. As a consequence, the security perimeter has expanded beyond the office building walls, and valuable data transfers now occur between remote devices, and IoT devices outside the corporate perimeter. This has made it easier for cybercriminals to successfully execute cyber-attacks.
Data Governance is crucial for all enterprise-level businesses
With heavy reliance on IoT and remote devices, organizations generate a large amount of data that needs to be managed effectively, securely, to protect sensitive data from unauthorized access, breaches, and misuse, while ensuring compliance with data protection regulations such as GDPR, CCPA, and HIPAA. Therefore it becomes imperative for businesses to adopt data governance to ensure the privacy and security of the users’ data is aligned with compliance. When data collection expanded rapidly, storage costs spiraled quickly up and new privacy regulations emerged. According to India’s recent budget, the Indian government has introduced a National Data Governance Policy, to help businesses with anonymized data which further improves data quality and compliance, builds trust and transparency, and provides increased flexibility As organizations are subject to various legal, regulatory, and industry-specific requirements related to data management, data governance helps organizations establish data management policies and practices that comply with these requirements, reducing the risk of legal and regulatory non-compliance, avoiding severe penalties, fines, and reputational damage.
Additionally, data governance improves data quality by minimizing data inconsistencies, errors, and duplication while capturing and storing data, enhancing the organization’s decision-making capabilities. It enables organizations to have a unified view of their data by ensuring that data is properly integrated, transformed, and exchanged between different systems, departments, and stakeholders. Today’s data-driven world also demands organizations establish guidelines and policies for ethical data practices to build trust among their customers, partners, and stakeholders, which can be achieved through proper governance.
In the digital transformation era, effective data governance programs need to tackle not just the staggering growth in data volumes, but also the complexities of cloud and hybrid architectures, as well as the growing reliance on advanced analytics. Additionally, the shift towards self-service data access and real-time applications has heightened the visibility and significance of data governance like never before.
How to adopt effective data governance practices
While most IT and business leaders acknowledge the value and importance of good data governance, they find it to be a complex undertaking, involving various aspects such as data quality, lineage, security, and more. Additionally, it demands substantial investments, and this financial burden and effort can be daunting for enterprise leaders, leading to their hesitation in addressing it. Nevertheless, with technologies evolving significantly, businesses have the advantage to utilize the best tools for data governance that considers the entire data and analytics lifecycle, instead of focusing on only a single capability.
An effective data governance tool emphasizes more on classifying and cataloging data as it is collected so that security and governance policies are consistent. Today’s organizations must ensure data accessibility for their users to enable smooth business operations and this entails managing data accessibility across various platforms, environments, and geographies, each with its own data compliance and privacy regulations. By associating data with access policies based on classification, organizations can enable the right people to access data in the appropriate format without constantly relying on IT for permissions. This requires a proactive governance strategy that focuses on driving business value through consistent and comprehensive access policies, rather than just reacting to regulatory requirements.
In addition, organizations need to control the security of enterprise data across various locations, including cloud stores, remote laptops, and data centers. Data security processes can vary based on network, encryption, and different industry standards that comply with adding layers of security. Disconnected security controls can result in some users being unable to access needed data, while inadvertently granting access to private data to unauthorized users. Therefore, organizations must adopt biometric and multi-factor authentication security processes to avoid disconnection and effectively secure data.
To ensure an effective data governance adoption, it is imperative for businesses to implement solutions such as Shared Data Experience (SDX) to enable secure data governance for hybrid architectures that span both cloud and on-premises data workloads. Organizations can easily locate information using metadata that maintains context across various analytics and cloud environments, compared to scanning through large data loads. Consistent data context simplifies data delivery and analytics, with a secure data-access model that can be used by multiple clients. Additionally, businesses can reduce risks and operational costs by ensuring consistent data context across deployments, enabling faster deployment of secured and governed data lakes, and granting more users access to data without compromise.
Future of Data Governance
In today’s scenario where data has become a strategic asset for organizations, effective data governance practices are vital for success in the digital era. Therefore, with growing resilience in data, we expect data governance to garner more demand in the upcoming years, and IT leaders’ increased focus and investment in data governance software.
(The author is Piyush Agarwal, SE Leader, Cloudera, and the views expressed in this article are his own)