Implement a Data Integration Strategy in the Cloud
Don't let your data drift away.
- The growing migration of business functions to the Cloud is having the neglected side effect of increasing the complexity of data integration (DI). The longer this problem goes unaddressed, the more data is being compromised and lost into the nether.
- Current DI solutions are often a series of hand-coded, point-to-point integrations with little consistency on the tool or approach used. Justifying the upfront cost of a DI tool can be difficult, but the unforeseen costs of poor data management can escalate at an alarming rate (storage, maintenance, hand-coding, etc.).
- Companies need to consider cloud integration upfront and approach it holistically, not on a project to project basis. Lots of work is going to be reusable from project to project, and implementing a holistic strategy from the start allows organizations to take advantage of this time and resource savings.
Our Advice
Critical Insight
- DI is the process of combining information stored in various sources to provide a unified view of the data, increase accessibility, and decrease inconsistencies. DI facilitates a single version of the truth; it brings consistency across an organization, which allows for the efficient use of data.
- The introduction of SaaS to an organization’s IT environment means the types of data transactions have increased to include:
- On-Premise to On-Premise data flows
- On-Premise to Cloud data flows
- Cloud to Cloud data flows
- DI solutions themselves have also begun to emerge from the Cloud. Consequently, organizations have three deployment approaches available to them as well:
- DI On-Premise
- DI as a Service (DIaaS)
- Hybrid (a combination of both)
- Organizations need to look to their own IT environments, examining the sources and flows of data, in order to identify what approach will best suit their needs in terms of security, performance, monitoring, and support.
Impact and Result
- Gather and refine data integration requirements by studying the data flows and data sources within the organization.
- Consider data integration tools as support for your DI management; DI tools free up developer resources and speed up development, testing, and deployment.
- After selecting and implementing the deployment approach (On-Premise, DIaaS, or Hybrid) that is most appropriate for your organization, make sure to have the right roles and responsibilities in place for continued DI monitoring.
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