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Cloud Data Integration: the best way to manage your business information

In recent years, many companies have been looking for a way to integrate all information in one place, and the solution is the cloud. Nonetheless, to reach optimum performance, it is necessary to know how to start a cloud migration process and its components.

What is Cloud Data Integration?

To understand the process we need to understand what Cloud Data Integration is. We could say it is integrating data that is spread in different systems, such as public or private clouds, or between cloud and on-premise systems. The main objective is to develop a single source of truth, where data is unified and enhanced to be consulted efficiently and transparently for users within organizations.

Like every tech process, Cloud Data Integration needs and detailed strategy for deployment.  Since every business has different needs, sometimes, the goal is to integrate multiple public clouds, set up a hybrid cloud, integrate on-premise systems with the cloud, or lift-and-shift migration among many others.

One of the most important advantages is the automation of processes that otherwise require manual intervention; it eases operations that require verifying, transferring, and transforming data. Operating manually can be very exhausting for staff members since it is time-consuming and also allows for human errors. This allows companies to spend their budget on areas that could be optimized with the use of technologies.

Whichever strategy you require, it is important to know its benefits and challenges.


10 benefits of Cloud Data Integration

Unlike a manual check, this practice improves data quality for better business performance. With an automation method, you can guarantee precise results in less time and make smarter more well-informed decisions due to the execution being precise. Let’s learn more about Cloud Data Integration advantages.


Graphic model that shows the benefits of Cloud Data Integration

Cloud Data Integration Benefits


  1. Accessibility: Storing data in the cloud ensures data accessibility throughout the organization. This facilitates all departments to exchange information or consult datasets for the next steps in the business process as long as they have proper access and permissions.

  2. Flexibility: Cloud data integration can be source-agnostic i.e, the ability to stage data irrespective of the source of origin. It allows enterprises to choose who can manage information. Additionally, with cloud integration, it is possible to define the way data is shared, analyzed, and used. You choose the limitations.

  3. Scalability: Updating data, software, and volume is easier than ever in the cloud. If you identify a new system for improving the processes, apply it! Your team and customers will thank you.

  4. Visibility: Cloud Integration allows for real-time detection of changes and adjustments from any collaborator with access to data, thus increasing visibility and preventing errors, and conflicts, while allowing issues to be fixed immediately.

  5. Data sprawl: As organizations grow, information spreads to various locations, and data becomes more challenging. Cloud Data Integration helps to bring data together into a single source of truth

  6. Adaptability to changes: Cloud Data Integration automatically handles data structure, semantics, and infrastructure changes thanks to tools like ETL pipelines, which reduce data drift.

  7. Budget control: When data professionals harness cloud use, organizations can control processes such as cloud storage and data handling per their needs. Businesses can make adjustments and use resources in other operations, which helps control costs in data storage.

  8. Synchronizing data:  Cloud Data Integration helps in getting a consistent view of data with real-time updates, which makes way for data integrity between transactional, ERP, and other IT Systems and end-user applications.

  9. Automating workflows: Forget about manually copying or entering data with Cloud Data Integration, since it helps automate organizational processes and standardize how data should be treated to extract its value.

  10. Redundant data: When the volume of data increases, it is common to see the same data in different IT systems. Sharing data stored during integration helps to eliminate duplications and synchronizing efforts.

As you can see, implementing Cloud Data Integration strategies can transform how businesses manage and facilitate competition in a dynamic Data-driven world. If your organization wants to gain an advantage over competitors, stakeholders must consider Data Integration as one of the most important steps to excel in a modern landscape.


Cloud Data Integration challenges

Now that you know the benefits of Cloud Integrations, it is time to tell you about its challenges. Evaluate the following 4 stages before deploying a project:

  1. Application Support: before choosing a cloud service provider suitable for your organization, you should question if the platform supports applications and software that your business has already deployed. Likewise, this provider must be able to connect with applications and software your operation might need in the future, to avoid efforts and costs due to a lack of compatibility.

  2. Ease of use interface: For guaranteeing data matches according to the company's needs like formats, rules, and credentials you must consider a user-friendly interface, this step is significant for all people who manage data and lack the technical skill set. 

  3. Security and Compliance: Similarly to Data Governance and Data Management, security and compliance are related to Cloud Data Integration. Before your company deploys any integration process, consider security standards and verify if the platform can fulfill requirements and current rules. Be careful to set the same security policies if you are using multiple clouds.

  4. All-in-One: Some platforms offer a more complete set of features than others. Some allow you to prepare, convert and verify data when the integration is being carried out. With the right cloud service provider, your company will get an infrastructure able to transform data, and therefore, the future.


Data Integration architecture

This is a transcendent element that helps with identifying data sources. It entails the designing of a pipeline that defines the flow of data between IT assets and your organizational processes, enabling interoperability through the systems.

Creating a Data Integration architecture allows the unification of disparate data, to enable decision-making and innovation in a world where data dominates all business fields.

Data Integration architecture allows an understanding of relationships between data and departments, tools, and metrics in a company. This process will allow for data silos to be deleted thanks to this technology. Moreover, it helps with understanding data behavior between internal and external people.

By getting an accurate architecture, the data will be ready to use and develop the next strategies for business. 


Why does Data Integration need architecture?

It is necessary since it is a guide for mapping, unifying, and delivering data across different sources. Moreover, this architecture must understand data for continuing further business procedures.

Also, the architecture enables better communication through the organization’s multiple departments, improving the performance and quality of products and services. 

Integration architecture management works in two ways:

  1. Service-oriented data integration architectures (SOA).
  2. Operational data integrations look at key performance indicators (KPI).

Data can be segmented according to its model, objective, scope, and architecture. Organizations should understand that they need to ally themselves with technology, strategy, stakeholders, and so on to empower their data.


Key elements of Data Integration architecture

In the world of data, many elements are connected. Here you will find some fields that involve Data Integration architecture:

  1. Data warehouse & data lake: Over time, data warehouses and data lakes have converted into an effective solution for storing and processing data more cheaply due to price tiers relating to data volume. For processing data, the first step is to store it while the last includes, in some cases, transforming data.

    Here is where another process appears: ETL (extract, transform and load). The main advantage of an ETL process is that is not linear, it can start whenever you migrate volumes of data and can be later transformed when the data scientist requires it.

  2. Real-time integration: The premise “time is money” also relates to data. For instance, real-time performance can detect errors in banking and finance. Likewise, through the use of data metrics and statistics, the sales staff of a fashion brand could anticipate what clothes will sell the best. Data helps to identify customer needs and give them the best experience with your services.

  3. Data Management: Data Integration architecture is only a piece inside the Data Management system. The way this piece is built will affect other pieces, as we can see in the next image, all are related. With data, you can make informed and result-driven decisions for all business fields.

  4. Digital transformation: The possibilities in Data Integration are big since it can harness new technologies such as machine learning and predictive models, which makes it possible to boost your processes. Enhancing other tools is a step forward in digital transformation.

Parts of the circle represent the fields that make up Data Management.
Architecture as a part of Data Management



Deploying Cloud Data Integration is equivalent to obtaining a 360 view of your data and a single source of truth. For businesses, it represents an evolution in every process and workflow thanks to accurate metrics, analysis, and strategies.

To harness data through Cloud Data Integration, the quality of the platform should be ideal and should contain the correct features to give you control of all information generated by your organization and your customers.

Arkon Data Platform allows all its users to manage robust data with an effective infrastructure for getting the right information. Through various features, you will be able to reach the greatest potential of your business via Data Pipelines and recipes, Business Process Workflow Engine, Data Governance, and more.

Our platform works in tandem with Arkon Data Solutions, a service that will guide you to enforce the precise data strategy.


Would you like to know more about our platform and solutions regarding Cloud Data Integration?


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