3 Cloud Integration Mistakes to Avoid

With the increase in traffic of data and applications to the public cloud, the need to synchronize that data between the company and cloud has greatly increased. While traditional approaches like enterprise date integration (EDI) have been used by several enterprises to resolve this problem, others are moving to specific and primitive approaches, such as simple FTP jobs or FedEx’d USB drive.
Cloud Integration

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Whatever be the approach, there are Three things every enterprise should avoid to achieve their goal: 

  1. The inability to define the actual meaning of the data: It is important to understand the data meaning and how it can be managed to avoid circumstances that can make it very difficult to figure out the right approaches to interchange data with public clouds and local data centers.
  2. The inability to understand bandwidth limitations: Transmission of data in the range of Gigabytes can create issues in the latency and bandwidth cost. This is a big issue since big data systems are built on public clouds, but the operational data for those big data systems remains in the enterprise.
  3. The inability to deal with error-handling issues: Issues related to the failure of data-integration solutions can affect data quality and lead to availability issues that must be corrected by people and not by the automated processes. Hence, enterprises are required to consider error-handling routines in both the cloud-to-enterprise data integration tools and on-premises.

To avoid these three things, strategise your actions by planning, analyzing and testing before final implementation.

This Guest Post is posted by Ng Wei Khang, CEO at Apixel IT Support. Ng Wei Khang started Apixel IT Support in 2004 with one goal in mind and that is to deliver high quality IT Support and Customer Support services in Singapore.

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