The cloud is now an accepted member of the enterprise IT family, as more executives discover the value of anything-as-a-service solutions. Simply put, cloud adoption is in full swing, and so far, the reports of improved agility, better scalability and lower spending are in abundance.
However, not every business can be so lucky to be able to seamlessly integrate their existing IT platforms into the cloud. As enterprises move their applications into the cloud, they uncover some challenges in regard to sharing data between software-as-a-service solutions, other cloud services and on-premise environments. The cloud promises to make IT environments less complex, but in the age of cyber vigilance and federal IT scrutiny, there are major concerns over where data resides, where applications live, and how information and services are protected.
Businesses need to determine how they pass data around their IT environments without exposing it to security risks, impeding application performance or reducing employee productivity. After all, this situation is all too common: Mission-critical applications share data with data analytics tools, and once analyzed, the insights are often transferred to a visualization tool. This was easy when all of those tools were located in the datacenter. Now what happens when each tool is a different SaaS solution? … Or from different cloud providers? There can’t be any hiccups in the process as data flows from location to location.
Many times, IT teams develop a “one-off” data integration strategy in order to connect an in-house application to a cloud solution. Then, another SaaS solution must integrate with a database in the cloud, causing those same IT teams to create a different approach for safely sharing data. This process will not hold up in the long run, especially since cloud services adoption is skyrocketing. According to a CIO article, within three years, a majority of organizations will have up to 27 different SaaS solutions. Having a separate integration strategy for each of those will cause problems over time, to say the least. The savings from implementing cloud in both time saved, and dollars could be overwhelmed by the integration costs if the organization does not plan carefully.
“Within three years, a majority of organizations will have up to 27 different SaaS solutions.”
Therefore, businesses need a universally applicable approach to cloud data integration. One-off point-to-point solutions create many individual links with their own issues to be secured and managed. A centralized integration point creates a ‘hub and spoke’ model that can reduce the complexity of the data integration model. IT teams can develop overarching strategies for these efforts, and then an organization can truly experience the full benefits of the cloud.
Where to Begin
As Network World reported, cloud data integration doesn’t require a wealth of technical experience, but rather IT administrators, managers and executives should set their sights on the business concerns. The source went on, asserting that successfully integrating on-premise systems with the cloud relies on the ability to “create, manage, restart and track sophisticated integrations.” This means that businesses should determine what’s necessary in regard to integration and how to accomplish those benchmarks.
Sharing data with cloud services sounds easier than it is in reality.
What are the business critical demands in this regard and what tools are useful? To address these issues the cloud industry has developed Solution as a Services offerings, such as Microsoft Azure BizTalk, Dell Boomi AtomSphere and MuleSoft CloudHub. Alternatively Data Platform as a Service (dPaaS) or Information platform as a Service (iPaaS), such as Liason’s Alloy Data Platform can also be used for both integration, data visualization and data consolidation.
Both of these solution types provide programmatic interfaces (APIs) into data “areas” of many common providers allowing IT teams to integrate data between providers and in-house applications via simple plug-ins. An example of where these plug-ins are used would be how to move data from your on-premise ERP running on SAP, to a company CRM running in the Salesforce cloud.
These tools also give you a solution that still supports a common data governance and security model vs the one off methodology.
Data governance is critical in that cloud applications are generally more accessible, and keeping tabs on your data is absolutely necessary. With that idea in mind, the primary focus of cloud data integration should be on security and governance. Creating a strategy that incorporates these two considerations might take some time, but in the grander scheme, the business will be better off with a comprehensive strategy from day one.
When it comes to security, the same ideal applies: What does the business really need? There are two kinds of data that need protection: data at rest and data in motion. For securing data at rest, organizations might need to segregate equipment or applications, storing – for example – intellectual property in isolation from everyday accessible data. Alternatively, for data in motion, encryption should be required in order to comply with typical industry regulations.
Cloud vendors and solutions providers play a role in cloud data integration with their tools and interfaces. But, architecture and integration standards are required in order to keep strategies consistent for years. Service contracts and SLAs are a great way to maintain performance with cloud services, but businesses also need to understand what systems they’re running and how they are encrypting data to find the best solutions.
IT teams should be considering cloud data integration software suites. These middleware-like solutions provide the plugins and APIs that create that interlink between resources. These tools along with a well thought out architecture and integration strategy will act as a standard mechanism for integrating every cloud solution.
The bottom line is that businesses have a lot to think about when it comes to cloud data integration. But with attention to the four areas mentioned above, successful data integration with cloud services and internal on-premise environments is right around the corner.
Source: Sky Chat IT Blog