Multi-cloud data governance is about handling data across different cloud services like Amazon Web Services, Microsoft Azure, and Google Cloud. It’s about making sure they follow the rules. But, managing data across these different services can be hard. When data is all over the place, it’s tough to bring it all together and keep control. To deal with these problems, businesses need a good plan for managing their data.
This means setting rules that apply to all cloud services, using tools to track data, and teaching staff to follow these rules. The goal is to keep data consistent, safe, and correct, while still enjoying the benefits of using different cloud services.
Forbes says that 90% of the world is starting to use more than one cloud service. But, a lot of businesses find this hard. Gartner thinks we’ll spend about $600 billion on public cloud services by 2023. At the moment, businesses use about 2.6 public and 2.7 private clouds on average. But, 82% find managing data hard, and 77.4% have trouble bringing together data from different clouds.
Data governance means setting up rules, procedures, and controls to make sure data is handled properly, kept safe, and used the right way according to the law. Even though using different cloud services can offer benefits like more flexibility, scalability, and cost-effectiveness, it can also make data governance more challenging.
A solution to this data management gap is the implementation of an enterprise operational data layer. This layer aligns with the demands of contemporary, worldwide applications and is built over existing data sources, promoting data interaction and eradicating data isolation and better Data Governance.
The Rise of Multi-Cloud Environments
As digital transformation accelerates globally, more companies are turning to a multi-cloud strategy. According to a Microsoft survey, over 25% of organizations worldwide are now using more than four cloud services for their operations.
In a multi-cloud setup, a company’s tech team selects the most suitable services from different cloud providers. Their choices are influenced by factors like specific requirements, location availability, and more. For example, they might use Google Cloud for creating software, AWS for storing files, and Microsoft Azure for handling their business data. This multi-cloud strategy can involve various types of cloud computing services, including Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), and Infrastructure-as-a-Service (IaaS).
This strategic shift towards multi-cloud environments offers numerous benefits that can significantly enhance a company’s overall productivity, work environment, and revenue. Here are the top four reasons why companies are making the switch to multi-cloud:
- Flexibility and Scalability: Multi-cloud environments allow companies to match their specific workloads to the cloud service that best fits. This flexibility facilitates scaling operations up or down as needed, optimizing resources and costs.
- Risk Mitigation: Using multiple cloud services reduces dependency on a single provider, minimizing potential risks related to service disruptions, vendor lock-in, and data loss.
- Performance Optimization: Different cloud services have unique strengths. A multi-cloud strategy allows companies to leverage the best features from each provider, improving the performance of their applications and services.
- Geographic Reach: With a multi-cloud strategy, companies can leverage the regional presence of different cloud providers to deliver their services more effectively worldwide. This approach ensures reduced latency, better performance, and a more satisfying user experience for customers across various geographic locations.
Data Governance in Multi-Cloud Environments
A multi-cloud approach, involving the utilization of services from various cloud providers, offers numerous benefits such as increased flexibility, reduced risk of vendor lock-in, and the ability to leverage the strengths of different platforms. However, this approach also presents unique challenges in terms of data governance.
One of the main challenges in managing data across multiple cloud environments lies in the complexity of these systems. The deployment and design of these cloud infrastructures often involve a network of servers, customized to meet the specific needs, size, and budget of a business. This complexity can complicate the tasks of data collection, storage, deployment, cataloging, backup, and removal.
Effective data governance, therefore, is crucial in making data work for businesses in a multi-cloud context. This involves creating robust policies and procedures that can navigate the complexity of multi-cloud environments. Moreover, these frameworks should address the potential risks associated with data security, compliance, and location in the cloud, while also identifying the value of data for storage and security purposes.
A key concern for many businesses utilizing multi-cloud strategies is data security and compliance. As data is distributed across different cloud platforms, the potential risk of data breaches increases. Ensuring regulatory compliance also becomes more challenging as data is often stored in different geographical locations with varying regulatory landscapes.
Furthermore, the management of data lifecycles becomes increasingly important in multi-cloud environments. This involves the regular cleaning of redundant data to improve efficiency and reduce costs. Similarly, improving metadata management and setting clear data integration policies are vital for ensuring the uniform implementation of data-security information across the different cloud platforms.
Lastly, the tracking and auditing of replica data sets are crucial for reducing redundancies across different cloud systems. Businesses also need to develop policies around preserving “original data” before they are analyzed and transformed, as well as archiving and managing data models effectively, especially when these are moved between different cloud systems.
Data governance in a multi-cloud environment is a complex but essential task. Businesses need to create robust and comprehensive data governance strategies that can effectively navigate the complexities of multi-cloud environments while ensuring data security, compliance, and optimal use of resources.
What’s needed is An enterprise operational data layer can bridge the gap in data management. It matches the needs of modern, global-scale applications and sits on top of existing data sources, enabling data exchange and eliminating silos. This ensures the continuous availability, performance, and scalability required by modern apps.
It also facilitates business continuity, prevents bottlenecks in cloud, mobile, and IoT applications, allows real-time updates, and is infinitely scalable. This kind of data layer provides the flexibility to create new data stores and streamline old ones as the business evolves. Moreover, it boosts operational efficiency and improves customer experience on apps and websites, which is crucial for business sustainability.
SCIKIQ as a Multi-Cloud Data Governance Platform
SCIKIQ is an all-in-one data fabric platform, that serves as an enterprise operational data layer capable of bridging gaps in data management. It streamlines the process of data integration, analysis, and governance across various sources, enhancing operational efficiency and decision-making capabilities.
SCIKIQ places a strong emphasis on data governance, cataloging, and compliance, offering robust features to manage and enforce data policies, maintain data lineage, and ensure regulatory compliance. This enables organizations to establish consistent data governance practices, improve data quality, and meet compliance requirements across their hybrid and multi-cloud environments. SCIKIQ’s data fabric platform provides the necessary tools and capabilities to establish a centralized data catalog, enabling efficient data discovery, data lineage tracking, and data access control.
SCIKIQ offers an all-visual, no-code platform for automated data governance, simplifying the process of managing and controlling your enterprise data. Key features of the platform include:
- Data Discovery and Cataloguing: SCIKIQ employs advanced graph capabilities for discovering and cataloging data assets. It includes the use of infrastructure on demand (POD) for data discovery, with services that search the database catalog, establish relationships, populate knowledge graphs, and make everything available on the front end.
- Data Quality Management: SCIKIQ identifies and resolves data quality issues through its built-in platform intelligence. It employs machine learning algorithms to eliminate human errors in data management, ensuring data accuracy and reliability.
- Metadata Management: SCIKIQ allows you to establish and enforce robust policies and processes for metadata management. This facilitates the seamless integration, sharing, and protection of various forms of information, including assets, glossaries, business data, and entities.
- Data Lineage: With SCIKIQ, you can capture full record-to-report data lineage for both operational and regulatory usage. Its comprehensive data lineage framework identifies duplicate resources, encourages module recycling, and provides a 360-degree view of the entire data journey.
- Authoritative Data Source: SCIKIQ helps ensure the authenticity and ownership of your data sources with its authoritative data source framework, which includes pre-configured roles for authorized access and easy maintenance.
- Automated Data Governance: SCIKIQ’s platform automates data governance policies, monitoring and controlling data quality, security, compliance, and privacy while tracking data lineage and usage. This enables real-time access to data, improved compliance and security, efficient management of big data, and reduced manual effort.
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Future Outlook of multi-cloud Data Governance
As the adoption of multi-cloud environments expands, multi-cloud data governance becomes critical. This ensures uniform, secure data management across all cloud platforms, enhancing agility and efficiency while reducing data breach and regulatory violation risks. The future will likely see increased multi-cloud adoption, escalating the demand for effective data governance tools. Organizations will also focus more on data privacy and compliance in an evolving regulatory landscape. Therefore, effective multi-cloud data governance will be pivotal to balancing adherence to regulations and leveraging multi-cloud computing benefits.