Enabling a truly data-driven organization by connecting cloud-based software assets
In comparison to the so-called “basic systems connectivity”, cloud integration together with cloud integration tools has fundamentally changed the way how companies approach the dilemma of siloed datasets and general data availability. While cloud integration has many advantages, the biggest benefits that businesses gain, by far, are:
- Real-time or near-real-time data updates across all relevant systems
- Opportunity to run a truly data-driven business thanks to connected data sources
- High degree of automation and speed, which results in faster reaction to the changing needs of partners, customers and users
Where there is SaaS implementation, there is also a strong need for cloud integration. It is, therefore, understandable why many analysts e.g. from Gartner or Forrester consider a robust cloud integration strategy to be imperative to success when companies move to the cloud to take advantage of cloud computing technology. A big part of this strategy are cloud integration tools that need to be chosen wisely and with relevance to the future requirements.
The role of Cloud Integration Tools
Cloud data integration is never easy because it requires a clear understanding of the systems to be connected including their APIs, knowledge about possible data exchange formats and patterns as well as different communication protocols, among many other things.
The goal of cloud integration tools is to remove at least some of these hurdles and by doing so, considerably decrease time-to-market for integration projects.
Such tools and platforms empower IT users and service providers to build sustainable integrations even when the technology stack will change in the future. Most cloud data integration solutions such as those from Cleo, Microsoft, IBM and others come with version control, security mechanisms, user-friendly configuration and data mapping, SDKs that allow a faster development of new endpoints and automatic updates of the available connectors.
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Cloud Integration Solution from elastic.io
The elastic.io’s solution has been built in and for the cloud from the ground up. It addresses all the common challenges including connectivity with business-to-business partners or API management and anticipates future challenges to come when organisations grow and expand their footprint in the cloud.
Decrease and save your operational costs
- Manage efficiently across multiple users with better user roles and different access levels
- Empower both seasoned integrators and ad-hoc developers
- Scale easily to fit your business process integrations needs
Deliver and scale integration projects faster
- Ready-to-use connector templates for key applications, updates & upgrades included
- Extract, transform and load data with minimal efforts
- Feed on-premises datasets into the cloud securely using a VPN agent
Welcome innovation by future-proofing integrations
- Prepare a standardised ecosystem for future use cases such as IoT or data mining
- Build pathway to a data-driven organization with event-based workflows
- Deliver integrated business processes for CX management, supply chain, and more
“I feel like we are nearing a point that we don’t need to justify why we would use tools like this, but we will need to justify cases where we do NOT use tools like this.”
– anonymous Stackoverflow user
Cloud Integration Types
The most common cloud integration types are data integration and application integration. The main difference between these two is the volume of data being transferred and the speed.
Typically, data integration implies data collection from several sources in a single repository, usually for later usage. Since there is no need for an immediate action upon this data, such jobs are done in batches over certain time intervals. Another hallmark of data integration is that it usually involves large sets of data that is raw and only gets transformed when necessary for a specific use case such as AI training or business analytics and intelligence. Other common examples for this type would be data migration and preparing the right environment for MDM.
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This type equally implies that datasets are moved from one source to another. However, such data is usually required in a timely manner – for example, when a new order placed by a customer or partner needs to be communicated from the order management system to the warehouse system, the customer management or sales system, and the finance system. Considering this, such integration jobs are, therefore, carried out much faster, in real- or near real-time and with much smaller datasets. Equally, the transformation requirements differ from that of data integration, since data must be transformed at the moment of its exchange between the several systems involved. In essence, this type of integrations reflects the everyday business processes.
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Cloud Integration: Related Topics
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