Cloud Data Integration: The Data Engineer's Guide (2023)

Data integration is the process of extracting datasets from different sources, in different formats, to transform them into meaningful forms and loading them to a centralized data warehouse. A cloud platform ensures immediate availability and real-time access to all the information as and when needed.

In this guide, you'll learn about cloud data integration, the benefits and challenges of cloud data integration, and explore different use cases.

We'll break down the best methods for integrating data in the cloud and unveil the best cloud-based data integration tools.

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.
That's when cloud data integration completes the picture beautifully. Here is how:

Agility

Cloud data integration is agile.
You are not bounded by hardware and software capabilities when deploying new integration patterns per changing industry scenarios. You can quickly connect to cloud applications and on-premises data sources to fetch enormous volumes of data.
This agility offered by cloud integration also assists data scientists, business analysts, and every other professional in your enterprise who deals with data, thus delivering the top-notch user experience just the way they want.

Flexibility

Cloud data integration helps you harness the power and reliability of cloud computing.
Businesses can process complex data integration mapping tasks and deploy and manage workloads capably.
Most cloud computing platforms come with auto-tuning and dynamic scaling, allowing you to process tons of data without server restrictions.

Enhanced competitive edge

Both the benefits mentioned above, agility and flexibility, translate to an increased competitive edge.
When your data professionals can access, edit, and share data anytime, it becomes easier for them to perform better and perform together.
Smaller businesses can think clearly and make educated decisions through proper data governance.
Bigger businesses can eliminate data silos and make quick key decisions.
Additionally, accessing data on the go also means increased customer satisfaction. It adds transparency between the customers and the business and makes related data accessible at the fingertips.

Better connectivity and visibility

Uncertainty, urgency, and unseen disruptions can prove costly for businesses. Businesses need to be ahead of time and on their toes to adapt to potential variations and innovations in the industry.
For instance, in the event of an unpredictable change in supply levels, companies with easy data visibility can respond calmly and tackle the change by making important business decisions as smoothly as possible.
Cloud data integration ensures minimum hiccups and that business operations continue smoothly as ever.

Operational efficiency

Cloud data integration offers enhanced speed and scalability. You can connect hundreds of data sources and integrate data within hours, if not minutes.
The advanced tools also rule out any chances of data redundancy and improve operational efficiency.
Further, as a large amount of data silos can be handled error-free, you need fewer users to run applications and administer the entire process. This also brings down the involved costs appreciably.
Not to forget, cloud integration involves no upfront investment in the form of on-premise solutions, and neither does it require any maintenance, thus further reducing costs.

What are the top challenges of cloud data integration?

Although cloud data integration offers a range of benefits we discussed above, it also has its limitations, like:

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.

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?

Cloud data integration empowers businesses and organizations with a number of applications, like:

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.

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.

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.

Database replication

Cloud database replication is the process of copying data from a primary server or instance to a secondary server or cloud instance. It ensures easy data accessibility, helps you with disaster recovery and improves system tolerance.

If done right, cloud database replication can help organizations squeeze more value from their data while minimizing costs and administrative burdens.

Methods for integrating data in the cloud

ETL

ETL, which stands for extract, transform, and load, is a standard data pipeline strategy to move data from a relational database to a data warehouse. As we will see, although various cloud-based tools help you with cloud data integration, ETL is still widely used. The process is simple. Businesses can use their existing ETL technology to source data, transform, and load the data in a target cloud platform. Here are a few ETL use cases to help you understand better.

iPaaS

iPaaS stands for integration platform as a service. As the name suggests, these platforms standardize the integration of applications, thus enabling quick data sharing between different applications. iPaaS introduces automation, thus helping you eliminate manual processes while improving speed, accuracy, and visibility.

Reverse ETL

In a conventional data integration process involving ETL, you extract the data from a relational database and other third-party applications and then transform it before loading it into the cloud data warehouse. Now, suppose you have a single cloud data warehouse that acts as an ultimate source of truth. Assuming you need to have a holistic view of your customers. Instead of switching or integrating different applications, you can extract all the required information from a centralized cloud data warehouse through a CRM or API. Thus, you no longer have to worry about different data sources and their accuracy.

Webhooks

Webhooks can be integrated with your cloud platform to import documents and transfer the parsed data automatically. For instance, you can import your documents from a cloud storage provider, parse them, and copy the parsed data to a CRM, a database, or a third-party application.

Data sharing

Cloud-native data sharing allows you to combine the import and export functions to move data across heterogeneous applications. If you have services running in the same cloud, you could copy or move data, provided it meets your use case and criteria. However, if you have data residing on two different clouds or multi-cloud environment, you must deploy replication techniques with the help of cloud-based data integration tools. Let's explore the best modern cloud-based data integration tools in the next section.

What are some modern cloud-based data integration tools?

Portable

Portable is the best data integration tool with 300+ built-in data connectors. If you want to fetch data from multiple data sources to derive meaningful insights, Portable has got your back.

Additionally, the team behind the data integration platform helps you with custom connectors on request with a quick turnaround time (read: a few hours) on the go. This data management tool also offers ongoing maintenance of connectors for no extra cost.

Talend

Talend meets both your data connectivity and analysis needs. It allows you to perform operations like data transformation and ETL without coding.

The tool integrates with all major cloud platforms. It offers connectors for Hadoop, machine learning, IoT, and more. Although the tool comes with a forever-free plan, its features are limited.

Jitterbit

Jitterbit is an iPaaS that deploys artificial intelligence technology to automate endpoints. The tool takes care of the full data lifecycle. It supports both cloud migration-based and on-premise data flows.

Its automapper feature with 300 prebuilt templates accelerates the data transformation process noticeably.

Informatica

Informatica is a suite of data visualization tools comprising of PowerCenter, Informatica B2B Data Transformation, and more. The tool renders support to both cloud-based and on-premise deployments.

If you are looking for a robust tool that will take care of all your data workflow needs, Informatica will tick all the right boxes.

Dell Boomi

Dell Boomi is the best data integration tool for hybrid cloud native infrastructures. This tool works fine with public clouds, private clouds, and on-premise deployments.

It has a graphical user interface, automation, and a reporting portal. The tool is speedy and enables faster connections.

Cloud Data Integration: Key Points

Data integration is no more a luxury but a need of the hour. According to reports, the global data integration market is expected to touch USD 19.6 billion by 2026.

And as many as 65% of organizations want to deploy data integration solutions from cloud platforms.

Rightly so, as we have seen, cloud data integration helps with a range of use cases, including data lake development, data warehousing, marketing, customer insights, database replication, and more.

Although there are various methods for integrating data in the cloud, most companies prefer automating the task through cloud-based data integration tools to speed up the process, eliminate redundancy, and rule out errors.

Portable is a data integration tool that handles all your data effortlessly, allowing you to focus on business processes rather than worrying about moving the data from point A to B. So, how far are you with your cloud data integration endeavors? Need help? We've got you covered.