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Benefits, Challenges, And Tools For Cloud Data Integration

There is a rising demand to integrate disparate cloud systems to keep pace with the proliferation of multi-cloud and hybrid cloud deployments. Cloud data integration can assist in synchronizing and sharing data across many apps, whether in the public, private, or on-premises cloud.

With HazenTech’s cloud data integration, you can easily share storage across your on-premises and cloud-based systems. We’ll go through the critical factors and problems of cloud data integration that can help.

What Is Cloud Data Integration?

data integration

Cloud data integration is used to automate complicated workflows and eliminate redundant data that may lead to operational errors. If implemented correctly, cloud data integration not only reduces the operating costs but can also boost the scalability, flexibility, and operational efficiency of your resources.

Between or inside public or private clouds, or between cloud-based and on-premises systems, cloud data integration is the activity of integrating data. Unified data repositories accessible to all relevant users and applications are the goal.

There are many well-established tools for data integration in public or private cloud platforms. Integration of public clouds, hybrid cloud environments, on-premise systems with legacy software, or lifting and shifting on-premise workloads to the cloud are significant challenges for enterprises today.

Integrating cloud data might be cumbersome if it is not automated and centralized. Admins must manually set up various integrations, test them, and ensure that data is sent correctly. Different cloud systems require distinct file formats, data structures, and data models for their data. Since many IT systems contain pre-built adaptors or connections, cloud integration is easier, faster, and less error-prone using iPaaS, an integration platform as a service (iPaaS). We’ll take a look at a couple of them here.

Cloud Data Integration Benefits

benefits data integration

If you aim to manage and analyze your business data efficiently, you want to reduce the number of programs involved. A minimal number of programs allow you to analyze your business operations and boost your company’s productivity tremendously.

Several key advantages can be gained by integrating data between cloud systems and between cloud and on-premises systems.

  • Synchronizing data—Assuring that IT systems and applications using the same data or entities have a consistent view of the data and receive regular, real-time updates is one way to synchronize data.
  • Automating workflows—Organizational procedures requiring manual copying of data or entry can be automated by integration, standardizing data treatment as it moves from one application to another.
  • Eliminate redundant data—The same data is sometimes stored many times in IT systems to serve the needs of various applications or processes inside an organization. Integration reduces storage costs and synchronization efforts by removing duplicate data and utilizing a shared data repository.
  • Flexibility and scalability—integrating systems allow operational personnel to improve procedures and identify new techniques that can provide additional value to internal and external customers.

Cloud Data Integration Challenges

Cloud data integration projects, on the other hand, may confront some significant hurdles.

  • Data movement—For large data volumes and high transfer frequencies, moving data from one cloud to another or between cloud and on-premise systems can be time-consuming, error-prone, or even impossible. Cloud data integration will fail if there are no plans to transfer data quickly.
  • No standardization—As far as data integration between cloud services and on-premise systems is concerned, there is no standard approach or protocol in place. Various cloud platforms, services, and resources use different data schemas and formats. Data interfaces and adaptors must be regularly updated to keep up with the ever-changing cloud services and apps.
  • Architectural issues—Problems with the architecture—many cloud systems are built with scalability or performance in mind, not data integration. Even with a system that can grow or shrink fast, it may be challenging to keep external systems in sync with the system’s data stored on dozens or even hundreds of cloud instances.
  • ETL—When it comes to data integration, sophisticated Extract, Transform, and Load (ETL) workflows were used to clean up and transform data for the target systems. Unstructured data and flexible data models are standard features of cloud computing systems. Data cleaning, treatment, and conversion are still required. Nonetheless, Consider how ETL can be performed without slowing down integration or adding a lot of complexity to your integration strategy.

Evaluating Cloud Integration Platforms For Data Integration

Enterprise-scale data integration initiatives nearly always necessitate the use of an integration platform, even for basic projects.

When evaluating cloud integration platforms for your project, keep the following factors in mind:

  • Specific application support—If you’re using particular programs, does the platform support them? Is it extensible and able to support any applications or data formats you may adopt in the future, and what is the effort involved in building a custom connector or integrating additional data sources via API?
  • How mapping works—Mapping data fields between source and target systems can be done using a visual interface provided by most integration platforms. If you’re mapping data, make sure the interface is easy to use for non-technical users. Make that it can manage the data formats, regulations, and exceptions specific to your company.
  • Security and compliance—Ensure all of your datasets are protected following industry standards and regulations. For one-time data transfers and ongoing data synchronization, see if the integration platform can meet your needs.
  • Data cleaning, preparation, and integrity: The integration platform should be responsible for cleaning and preparing the data and confirming its integrity before using it. The data stream that your target application expects will not be created unless you have other tools or methods in place.

Cloud Data Integration and HazenTech

As part of your cloud data integration plan, HazenTech can assist you with integrating your data. A single pane User-Interface allows users to control, automate, and orchestrate all your storage resources, no matter where they’re located, whether they’re in a hybrid or multi-cloud architecture. As a result, HazenTech makes it easier for you to move, replicate, and synchronize data between multiple data sources and platforms.

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