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Data Integration Challenges in a Siloed World

Modernizing your infrastructure and operations means breaking down “silos” — including those that hamper your data integration processes. Here’s a look at the silos that typically stand in the way of data integration, and what businesses can do to tear them down.

“Breaking down silos” is lingo that you’ll hear if you follow the DevOps movement. Part of the point of DevOps is to eliminate the barriers that typically prevent different types of IT staff — such as the development and the IT Ops teams — from collaborating with each other.

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According to the DevOps mantra, everyone should work in close coordination, rather than having each team operate in its own silo. Silos stifle innovation, make automation difficult and lead to the loss of important information as data is transferred between teams.


Silos and Data Integration

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Although the DevOps movement focuses primarily on software development and delivery, rather than data operations, the value of tearing down silos is not limited to the world of DevOps.

The same concept can be applied to data integration operations — especially if you embrace the DataOps mantra, which extends DevOps thinking into the world of data management.

After all, the typical business’s data operations tend to be “siloed” for a number of reasons:

  • Businesses have many discrete sources of data, ranging from server and network logs to website logs, digital transactions records and perhaps even ink-and-paper files. Because each type of data originates from a different source, building a single process for integrating all of the data into a common pipeline can be challenging.
  • Different teams within the organization tend to produce different types of information, and they may not share it with each other. For example, your marketing department might store data related to customer engagement in a recent offline ad campaign. That data might be able to provide insights to website designers, who could use it to determine how best to engage customers online. But chances are that your marketing team and web design team don’t communicate much, or share data with each other on a routine basis.
  • Modern IT infrastructure tends to be quite diverse. Your businesses may use a combination of on-premise and cloud servers, with multiple operating systems, Web servers and so on in the mix. Each part of your infrastructure produces logs and other types of data in its own format, making integration hard.
  • Young data and historical data are usually stored in different locations. You probably archive historical data after a certain period, for example, possibly off-site. In contrast, real-time data and near-real-time data may remain in their original data sources. This also leads to data silos because data is stored in different places depending on its age.

How do you destroy these silos? The short answer is data integration.

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Data integration refers to the process of collecting data from disparate sources and turning it into actionable information. Data integration typically involves data aggregation, data transformations, and data visualizations.

The end goal of data integration is to turn data into information that can deliver meaningful insights to people reviewing it, without forcing them to think too hard in order to find those insights.

If your data remains siloed, data integration is nigh impossible. You can’t achieve easy, obvious insights if you have to look in multiple places to find data, or if complementary data produced by different teams or machines is not combined together.

Nor can you integrate data effectively if your organization is siloed. Everyone should be able to view collective data insights in the same place and at the same time, so that they can also communicate in the same place and at the same time.


In short, your data, and the teams that work with it are probably spread across disparate locations. In other words, they are siloed.

Deriving maximum value from your data requires breaking down those silos through data integration.

For more Big Data insights, check out our recent eBook, 2018 Big Data Trends: Liberate, Integrate, and Trust Your Data, to see what every business needs to know in the upcoming year.

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