What is Cloud Data Integration?

• Cloud data integration is the process of collecting data from applications, systems, repositories, and IT environments in a cloud service (say, Google Cloud, AWS, Microsoft Azure, and so on).​
• The data exchange happens in real-time, and since the data is integrated into a cloud platform, it facilitates easy access over a network.​
• In other words, cloud data integration involves configuring different applications such that they can communicate with each other and share big data in cloud systems.​

What are the main benefits of cloud integration?​

• As the name indicates, data integration brings datasets from different sources together cohesively without compromising the data quality.​
• Deriving insights from complex real-time analytics requires more than one data type from more than one source.​
• Assuming you are an e-commerce store or a seller on Amazon, deriving insights from data would mean combining order management, inventory, and customer data to understand your customers better.​

What are the top challenges of cloud data integration?​Data migration​

• Cloud data integration involves transferring data between multiple cloud-based apps, systems, and databases.​
• It is a complex task that is also prone to errors. It can also be time-consuming, assuming an enormous amount of data is involved.​
• Further, if exceptionally high volumes of data are involved, it could even become impossible to migrate.​

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Compliance​

• When dealing with data, it is important to comply with related regulations. Think GDPR, HIPAA, and countless other requirements.​
• It is highly recommended to choose data integration software that complies with all the required regulations depending on your industry.​

Security and data privacy​

• Security is always a concern when dealing with the internet. If you are working with cloud data companies, you could be prone to online threats like data destruction, data theft, and ransomware.​
• This is why it is important to close all backdoors. As a rule of thumb, always choose a reputed integration service provider with all the security measures in place.​

Lack of standardization​

• Data integration between different cloud platforms is another hurdle you need to cross. The hurdle is even bigger if you need to establish communication between the cloud and on-premise systems.​
• This is because no standard protocol could make the systems communicate. This is why updating data connectors and adaptors associated with different cloud platforms and services is highly recommended.​

What are some top use cases for cloud data integration?

Data lake development​

Consider a data lake as a centralized repository to facilitate easy storage and processing of enormous amounts of data, whether structured, unstructured, or semi-structured.​

Cloud data integration provides a cloud-hosted storage platform for meeting all your data needs, including analysis and insights synthesis.​

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Data warehousing​

Data warehouses have been the backbone of enterprise analytics and reporting for years. However, they were not designed to handle the tons of data that today's organizations deal with.​

Cloud data integration ensures you are not constrained by physical data centers and can dynamically scale up or down your data warehouses. Furthermore, cloud-based data warehouses store data in a highly structured and unified manner, ready to be used for an array of business intelligence and analytics use cases.

Marketing​

Cloud data integration ensures easy access to data from different sources, thus empowering marketing teams with crucial insights. They can run hyper-personalized campaigns and deliver a wholesome experience to their target audiences.​

Furthermore, cloud data integration also revolutionizes marketing campaign optimization, lead routing, real-time reporting, and more.​

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Customer insights​

Customer data integration helps you collect and organize customer data for easy sharing. Data synchronization allows your customer support team to assist customers based on real-time data transfer. Your marketing team can further use the data for tailoring campaigns as per the customer data, and so on.​​​