Cloud Data Integration: Examples, Benefits, Tools

What is Cloud Data Integration?

Cloud data integration is basically a way to combine data from multiple different sources into a cloud-based system. A few examples of this include using a data lake, data warehouse, or a relational or non-relational database. It is important to note that this integrated data can originate from a cloud-based database or even applications. In this case, they can be on-site systems or a combination of both. The main objective is to develop a unified data store that is more accessible, efficient, and transparent. This leads to a system that is capable of providing better support and making more accurate business decisions for users.

Over the past few years, the growth and usage of technology products and services have significantly increased. Services such as big data, the Internet of Things (IoT), software as a service (SaaS), and cloud computing have boosted the volume and variety of data sources available. Typical, this type of digital data was stored in isolated silos, and this caused problems because it became much more challenging to gain business insights. These shortcomings have been resolved by using cloud data integration because it is able to move, discover, and put together data from different sources. The biggest positive here is that it can assess insights, support machine learning, and make the best use of advanced analytics data. Companies can quickly become much more competitive by implementing this process, and improvements can be seen across digital operations and customer satisfaction.

When it comes to incorporating cloud data integration into business processes, the needs of the business must be taken into account. The process usually involves batch processing, real-time event stream, APIs, and different pipelines. Two standard pipelines are ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform). Data integration is relatively mature inside public cloud providers like AWS, making them easy to use. However, difficulty can occur if you are trying to integrate multiple public cloud systems, set up hybrid cloud environments, or integrate on-site legacy systems into a cloud workflow.

A drawback worth mentioning is that if there is no automation or central control, cloud data integration can be significantly time-consuming. Administrators are responsible for manually setting up all of the integrations, testing them, and verifying that the data is concise and accurate. In some cases, the data even needs to be transformed to fit the correct formats of other cloud platforms. One of the best ways to do this is using an Integration Platforms as a Service (iPaaS) as they offer ready-made adaptors for numerous computer systems, and this can eliminate the need for troubleshooting as it is more likely to work out of the box.

Benefits of Cloud Analytics

There are many advantages to using cloud data integration with cloud analytics. The biggest gain for companies can be seen when they utilize cloud data integration to take a more in-depth look into the insights of their data. The first standout advantage comes from agility, with companies now able to rapidly adapt and deploy new changes whenever there are new trends in the digital market. With the capability to connect on-site data sources to cloud applications, new doors can be opened, allowing companies to incorporate large sets of data and giving users the power to make better decisions. Another advantage is that cloud data integration significantly improves speed as it can enable faster building and implementation of complex integrations at a level that was not possible before. These improvements come as a result of being able to use pre-made templates and mappings that can be reused multiple times to connect lots of applications and data sources.

One of the other benefits that can be achieved is improved flexibility. When using cloud data integration, processing complex tasks becomes considerably more accessible, as does managing modern workflows, as it makes the best use of the power attained when using computers. In the case of Serverless Spark engines that can have dynamic scaling and more fine-tuned automatic abilities, they are better suited for handling big data as they are not limited to physical servers. They can deliver elastic storage as a solution that is more than capable of scaling based on the size of the volumes, and this can give cost-saving benefits when a platform offers pay-as-you-go services to customers. Another bonus worth mentioning is that this process is suitable for remote work because IT resources can be accessed from anywhere in the world. It has security features baked in for encryption and backups.

As you can see, Cloud data integration provides a wealth of benefits, such as:

Agility 

With cloud data integration, companies can quickly adjust to new market trends and changing business strategies. Cloud computing also speeds up deployments and allows for the implementation of new integration patterns. The most significant advantage here is that this guarantees that users, business analysts, and data scientists have fast access to the data they require.

Speed

As pre-built templates and reusable mappings are created in advance, cloud data integration can be used to streamline the building and running integrations. With these improvements, companies are better able to connect multiple applications and data sources, making it far easier to create enterprise-level applications in much less time.

Flexibility and Scalability

Because of cloud data integration's computing power, completing complex tasks and managing multiple modern applications can be considerably simplified. You can use elastic storage solutions, which can then be scaled up or down depending on your needs and the data volume you are using. The added cost benefit here is the convenience of using a pay-as-you-go service.

Enhanced Data Accessibility

Integrating data from different sources into one cloud-based system is one way to make sure that data can be accessed by all users and applications connected to that system. When using this integration, companies no longer need to worry about having data silos as it's now possible to have improved collaboration with data sharing across an entire organization, and this leads to much better insights and decision-making for a company.

Cost Efficiency

As there is no need for a physical on-site setup, areas like physical infrastructure costs and maintenance can be eliminated. The result of these improvements is having to worry less about operating costs. The pay-as-you-go services model totally removes outdated data, so the costs of running the data side of the business are more manageable.

Automation and Error Reduction

Cloud data integration platforms have automated tools that can speed up the workflows and, as a result, decrease the complexity that can come from too much manual work. This means fewer errors and better data consistency across the board for all connected applications and computer systems.

Cloud Data Integration Use Cases

The thing that makes cloud data integration so unique is that it is essential when used across different industries as it can boost business productivity and decision-making, and all data sources can be put together inside of one unified system. When inside of a retail environment it can enable real-time inventory checks and more personal customer experiences as it integrates data from both online and offline sources. The benefits to healthcare can be seen via better patient care and efficiency that can come from electronic health records or medical data on devices that can support a wealth of advanced analytics information. Within a financial environment, cloud data integration makes for better decision-making and fraud protection as the data from accounting, CRMs, and marketing departments is combined making for an easy read. The real-time analysis and compliance reports help with scalability and flexibility as companies become better suited to adapting to changes in the market.

Real-time Inventory Management in Retail

When data is integrated from online and offline sales channels into a cloud-based system, retailers can monitor inventory levels in real-time. This means that retailers can predict demands with greater precision, which is good for optimizing stock levels. Enabling personalized marketing campaigns now becomes more practical, and this can result in much higher customer satisfaction and better overall sales performance.

Enhanced Patient Care in Healthcare

Data is now maintained in one place, and this can include health records, laboratory systems, and medical devices, all stored in a central cloud database. This type of integration means that patients have up-to-date information that is accessible across all medical departments. Advanced analytics is supported for predictive modeling and tailored treatment plans. Data privacy, compliance, and security are also taken into account.

Fraud Detection in Finance

Financial institutions are able to use cloud data integration to combine the data from multiple departments into one. This can come from accounting software, customer relation management systems (CRM), and marketing data feeds. The advantage of having such a data approach is that it gives the company real-time financial analytics and fraud detection. As a result, the workflow is more streamlined, and there are much fewer manual errors caused by human data entry errors. With this scale and flexibility, cloud solutions allow financial companies to handle significant transactions with ease.

How to choose the right cloud data integration platform

Choosing the right cloud data integration platform is essential because you need to have a platform that can offer reliable data flow and provide sound business operations. When taking the time to evaluate potential platforms to use it's a good idea to look into a few critical factors. These factors can help your company to better meet its needs and determine the most ideal workflow for your data integration projects. Making sure that the platform has support for current and future applications, has a user-friendly interface, and has robust security features will give peace of mind.

Take the following into consideration when going through your options and choosing the best tool for your use case:

Data Storage

Try to evaluate the platform's data storage capabilities to ensure that it can handle the data volumes, types, and formats that you need. You must also consider whether the platform can offer scalability and storage solutions for when you grow. Check that it supports both structured and unstructured data volumes to enable good interoperability.

Cost

Guarantee that the platform's pricing model is in line with what you expect for your budget and ideal usage costs. Investigate to see if the pricing structure is transparent, like having subscription or pay-as-you-go options, because unexpected costs are never a good thing. Look for hidden fees for storage, data transfers, and other features, and look at the overall cost of ownership.

Maintenance

Be mindful of the maintenance requirements the platform uses. These can mean updates, support, or troubleshooting. If the platform allows for automated maintenance, then it is worth considering, and the same applies to very strong customer support as this can limit downtime and give you more safety as it is likely that the operations will be reliable. If the supplier has regular updates and other features up to date with future-proof technology and security then you can consider it as one of the better options available.

Experience the unparalleled efficiency of Matillion’s data management platform

Matillion makes it easy for businesses to control their data as powerful and user-friendly solutions can be used to streamline operations. If you are trying to find a management platform that works well at integrating advanced data sources while also giving you access to real-time analytics, we deliver on scalability, and efficiency and have the agility to get the job done. 

With Matillion your data is streamlined which means that you get access to automated data pipelines that reduce thinking and make it faster for you to concentrate on what really matters which is making decisions. With scalability enabled it's easy to adapt and scale your business as it grows adding new data volumes when necessary. Your data is always secure, compliant and ready to be used at all levels in your business thanks in part to having a high data governance standard.

Want to see how good Matillion is at transforming data? Book a demo to see how effective a modern data platform like Matillion can be at serving your business project requirements.