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Ensuring Reliable Data Integration

Posted by Edaise Germany on Oct 5, 2019, 2:55:22 PM

Data Integration – The combining of data from different sources into one source.

If you are a systems analyst, data integration may become second nature at one point, however until then, it can take some practice and reassurance that everything has been integrated correctly and thoroughly. Data integration often includes working with an application programming interface (API), which is an interface which allows two applications to interact, or talk, with each other. Having a reliable systems design that integrates disparate and distributed data can help data be read in a new and unique way. Aren't you curious to see what your newly integrated data could reveal? This could help your business gain new insights and advantages, and therefore increase business performance. Before any analytics can be performed on data, it must be integrated properly, which is why ensuring that you have integrated your data properly is significant.

Problems & Difficulties of Data Integration

Some problems could include: uncertainty of data, management, syncing across data sources, finding insights, and skill availability.

  • Finding a systems analyst to employ could be difficult, as there is a need for more people in the field.
  • Even though integration tools may be used, it is not uncommon to face tool incompatibility, so double check that the integration tools you are planning to use actually work with each other.
  • If you do not have a plan with specific steps to integrate Big Data, havoc could be wreaked, as some companies may want to jump from project to project, and if you do not have tracks to look back on, you may not know where you left off or when, so make sure to have an action plan which will assist in you following through and finishing anything you start.
  • Don't take technology for granted! Explain to anyone who is ignorant why and how data integration will save time and money in the long run. 

How Do I Ensure Reliable Data Integration?

  • Use the right, compatible tools
  • Have a plan
  • Acknowledge the importance of Big Data integration

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