In today’s multi-cloud world, standardization works like a translator for cross-cloud data sharing, ensuring that different cloud platforms can read the data and enable a seamless exchange.
Let’s say you have multiple offices around the country, each with a different security system, office manager, and opening hours. But you need to access the company files safely and securely from any location. That’s the challenge of cross-cloud data sharing. And it’s a big one, with 85% of businesses using two or more cloud servers and 25% using at least five.
With each cloud provider acting as a separate office, this can lead to difficulty accessing all the files you need. Plus, having multiple offices with different points of access makes you vulnerable to break-ins and data breaches. Although there might be restricted areas, or safe rooms, within the office buildings (storing data subject to complex privacy regulations) that require special access permission, does every office building have the same level of security?
Luckily, solutions exist that can make sure they do.
Let’s dive into the typical obstacles businesses face due to cross-cloud data sharing and a range of possible solutions to help you unlock real-time insights.
The challenges of multi-cloud data management
In a multi-cloud environment, data is spread across different cloud platforms with varying storage solutions and management tools. This type of decentralized framework can lead to fragmented data ownership, limited visibility, and data silos.
Data silos prevent businesses from gaining a holistic view of their data. Silos facilitate incomplete and inconsistent data sets meaning one department may be accessing wrong or outdated information. This hinders the ability to generate comprehensive real-time insights, facilitate collaborations, and make data-driven decisions. In fact, an XPLM study found that 76% of respondents admit that data silos curb cross-departmental exchange.
Furthermore, each cloud provider a business uses represents another security issue, with each cloud being a potential entry point. Network scans are a popular way for cyber criminals to identify exposed entry points. Many use a technique called port scanning, which is the same way auditors find vulnerable network areas. Attackers then target vulnerabilities or misconfigurations between cloud platforms to infiltrate a business’s entire cloud environment, potentially causing catastrophic damage to a business’s finances and reputation.
Multiple clouds also mean it’s hard to maintain an overall view of potential security risks and ensure consistent security policies are enforced everywhere. This is further exacerbated due to data silos and with each cloud provider having its own security protocols and configurations. A Radware report found that 69% of organizations experienced data breaches or exposures due to variations in how application security was configured across different public cloud platforms.
Another significant issue of cross-cloud data sharing relates to data privacy regulations, such as Europe’s General Data Protection Regulations (GDPR) and the California Consumer Privacy Act (CCPA), with many different countries and states having differing data collection, storage, and access requirements. Businesses must comply with the regulations applicable to their business type, the location of the data, and the users accessing it.
Ensuring compliance across multiple cloud locations adds significant complexity to data governance processes and means additional resources and expertise are required to manage compliance across different regions. Staying compliant may be a relatively easy challenge for large enterprises with extensive IT teams. However, for startups and small businesses who may not have an in-house IT team, staying afloat of ever-changing regulations could require them to spend much of their limited budget on expert cloud architects.
See also: Streamlining Multi-Cloud Ecosystems with Supercloud
Solutions for cross-cloud data sharing
While a multi-cloud approach does have its challenges, with more businesses collaborating internationally, establishing work-from-home initiatives, and outsourcing projects with specific specialties, it’s essential for IT teams to share data. Here’s how they can do it safely.
Standardization across cloud platforms
Put simply, standardization works like a translator for cross-cloud data sharing, ensuring that different cloud platforms can read the data and enable seamless exchange. This eliminates the need for complex custom code or data transformation processes for each cloud environment.
Organizations such as the International Organization of Standardization provide independent, non-governmental, and global standards for businesses to follow. For example, you can find and purchase information regarding the top standards in the industry. ISO/IEC 23894:2023 guides users on how to develop, produce, deploy, or use products, systems, and services that use AI.
Following standardized data structures facilitates real-time data analysis, removes bottlenecks, and avoids delays or disruptions in data sharing. And importantly, standardized data simplifies data management, making implementing consistent data governance policies easier across multiple cloud environments.
Centralized data lake
To make the most of multi-cloud environments, enterprises should combine and centralize their data inside a single database—or data lake. Since these repositories can hold and process vast amounts of structured, semi-structured, and unstructured data, they are great for cross-department collaboration. To enable flexibility of data sources, you might implement a “schema on read” approach. This means defining the data structure during analysis instead of enforcing a schema upfront.
However, centralized data lakes can be configured to process data in near real-time. Consider pre-processing steps to prepare unstructured data for faster analysis. This could involve extracting relevant features or metadata beforehand. You can then analyze the pre-processed data in near real-time alongside your structured data streams.
This is where AI-powered data catalogs come in: These work as a search engine for the data lake, using AI and machine learning to:
- Automatically scan and classify data within the lake, making finding and understanding relevant datasets easier.
- Identify and address potential inconsistencies, such as duplicate or missing data, ensuring its accuracy and reliability for analysis.
- Track the origin and evolution of data sets, providing valuable context for analysis and ensuring regulatory compliance.
By leveraging data lakes with AI-powered catalogs, businesses gain a powerful solution to cross-cloud data-sharing obstacles. The data lake centralizes information, while the AI catalog unlocks the data, making it understandable and trustworthy.
Third-party data-sharing platforms
Third-party platforms allow companies to connect their various cloud environments to the platform, allowing for secure and controlled data exchange. This central hub simplifies cross-cloud collaboration, enabling departments across cloud environments to access and share data easily, fostering collaboration and knowledge sharing.
Plus, having a centralized data focus point simplifies data governance tasks like access control, compliance monitoring, and audit trails. Therefore, with faster and more efficient data sharing possible,
Also, some platforms offer visualization tools, like built-in dashboards. Businesses can understand data at a glance and react to market trends and opportunities quickly, enhancing their overall agility.
There’s a large variety of platforms and tools on the market, including data integration platforms—like Informatica Cloud Data Integration and SnapLogic Cloud Integration Hub—and cloud data warehouses with multi-cloud support, such as Snowflake.
Having a third party to provide features like built-in reporting, provide detailed audit trails, and employ robust security protocols like encryption at rest and in transit takes the burden of a small IT team and individuals, but it’s essential to make sure your partner is trusted.
Choosing the right platform and tool depends on a business’s specific needs and budget, so companies should consider which cloud providers are supported, the security features they offer, and whether the platform can scale with the business.
Wrapping up
The current multi-cloud approach presents a challenge for businesses. Fragmented information locked away in multiple cloud environments denies access to real-time insights and increases issues regarding compliance and regulations, not forgetting that numerous entry points increase the attack surface for hackers.
However, businesses aren’t helpless to the cause. By standardizing data formats across platforms, implementing a centralized data lake with a robust data catalog, and leveraging third-party data-sharing platforms, there is light at the end of the tunnel. And this light can help businesses break down data silos and unlock the true potential of their information.
