According to an IDG survey, enterprise data volumes are increasing by 63% on average, with 90% of the surveyed companies using cloud data warehouses for data storage. With this increase in volume, businesses need to consolidate, clean and transform their cloud data faster to get valuable business insights. Cloud data integration products can help streamline and accelerate the cloud-to-on-premise or cloud-to-cloud integration process using automation, allowing businesses to free up their time and resources.
In this post, we will discuss the need, benefits, and challenges of cloud data integration, go through a sample use-case, check various steps in the cloud integration process, and delve into the details of choosing the right cloud integration software for your business. So what is cloud data integration? Let’s begin
What is Cloud Data Integration?
Cloud data integration involves the consolidation of disparate data from multiple systems where at least one endpoint is a cloud source such as Azure SQL, Google Cloud SQL, Amazon RDS, Oracle Cloud Database, Snowflake etc.
With data scattered across multiple cloud sources, finding business-critical insights becomes a challenge. Cloud data integration helps consolidate, transform, and clean this data to give business users a 360-degree view of all important enterprise interactions. This can then be used to drive insights from and make better business decisions. Now that you know what cloud data integration is, let’s move on to its benefits.
Benefits of Cloud Data Integration
Businesses use cloud-based integration tools or services to capitalize on the following benefits:
- Data compliance: Companies need to store and maintain customer data according to industry standards such as HIPAA, GDPR and PCI DSS to ensure security of this sensitive information. Using enterprise data integration software, businesses can easily set up workflows in place that help meet these requirements.
- Data synchronization: Businesses may use different systems por applications for different teams, and one major challenge in this case is the existence of duplicate records on different systems that have inconsistent data due to updates. Cloud data integration ensures that there is the same information on all systems that is updated in real-time. This removes the possibility of errors in analysis and decisions based on incorrect data.
- Process automation: Manual data entry and duplication is prone to human error and usually consumes a lot of time. Automating data integration to cloud streamlines and accelerates the process and allows businesses to allocate their valuable resources elsewhere.
- Data modernization: Some companies that have been using legacy systems and have accumulated years’ worth of data find it difficult to shift to modern cloud systems due to the sheer bulk of data that needs to be transformed and migrated. With cloud service integration tools, legacy data can be easily transformed and loaded to the desired cloud destination.
- Business scalability: Cloud data integration helps eliminate data silos through automation of processes and allows businesses to manage any volume of data with workflows and powerful ETL engines. This ensures that a company can scale up any time without worrying about manual, time-consuming tasks like data entry and execution of SQL queries.
Integrating data between cloud systems or between cloud and on-premise systems presents its own challenges that businesses need to keep in mind before they look for solutions. Following are some of the most common issues:
- Moving high-volume data with accuracy: Moving high volume data to or from the cloud while ensuring data accuracy is a tricky process. It requires comprehensive strategies in place so that the migration can be error-free while meeting the frequency requirement of the data transfer.
- Complex ETL processes: Extracting, transforming, and loading data to or from the cloud is a humungous task, the complexity of which is directly proportional to the volume and veracity of business data. Writing code for this task is also quite time-consuming. This can be mitigated by using a cloud-based data integration service or software that replaces manual jobs with automation and helps simplify the complete ETL process.
- Choosing the right cloud integration software: Choosing the right tool for a business’ use case is one of the most important challenges of setting up a cloud data integration automation platform. The chosen solution should be able to perform sophisticated integrations and meet every requirement of the use case so that the company would not need another tool to meet the remaining needs.
What to Look for in a Cloud Integration Software?
When looking for the right enterprise data integration software, here are some considerations to keep in mind before making the final call:
- Meets all project needs: Every business is different. When choosing cloud-based integration tools, it is imperative to make sure that the platform checks all boxes of the specific use case needs. This means identifying elements that are must-haves and confirming with a (preferably live) demo that the platform offers all features that are required
- Connectivity: The tool should have built-in connectors for the file sources, databases, and applications that are currently in use by the business or may be adopted later. Ability to connect with APIs is a bonus that can ensure that your data architecture can integrate data from new applications in the future
- Ease of use: When searching for cloud integration products, users may find out that there are many tools that can provide a solution to the same business use case. In this case, the best filter is to identify which software is the easiest to use. A software with a shallow learning curve will help save both training time and the time to create complex integrations
TheChemLabs is a world-renowned company in the manufacture and distribution of chemical products. They cater to customers in multiple industries across the globe. Each country has a business unit that stores the customer, production facility and distribution center data in their internal systems. The data comes from multiple sources and is in different file formats, which makes it difficult to analyze and gain insights from.
This scattered data hindered the company to gain business-critical insights. To gain a 360-degree view of their global interactions, they decided to consolidate the disparate data to a cloud data warehouse. They chose Amazon Redshift for its ease and performance. Now all that was left to do was to implement this bulk data integration to the cloud.
The main challenges in this project were:
- Complexity: TheChemLabs had multiple data sources for their data, and the sheer volume of it increased the complexity of the project. Moreover, some records were stored in mainframe systems like , and modernizing this data for the cloud was another struggle.
- Time: Writing code for such a project would be immensely time consuming, not to mention that there would be a good chance of human errors
- Ensuring seamless, error-free integration: Consolidating disparate data from multiple sources, correcting data duplication, transforming data into required formats, and setting up data validation checks were essential components of the project
Working on the project in-house was not an option for TheChemLabs and they started looking for enterprise data integration software in the market that would serve their needs. After reviewing multiple platforms and their features in detail, they ‘s native connectivity to cloud databases like Redshift made the data movement easier. Moreover, the various database write strategies in Astera Centerprise like incremental updates, rule-based updates, record synchronization, and slowly changing dimensions allowed them to implement advanced logic when writing a dataflow to the destination.
Using Astera Centerprise to Execute Data Integration in the Cloud
Astera Centerprise is a powerful cloud integration software with robust options that help simplify and streamline business processes. TheChemLabs found the in-built transformations and drag-and-drop data mapping extremely helpful to manage their data and ensure data compliance.
The built-in data quality and validation features also helped TheChemLabs to make sure that the transformed data was error-free before using Astera’s native Redshift connector to move data to the destination.
Sample 2:Dataflow with a data quality check on one error-prone element of source data before being mapped to the destination table
Data Integration Automation
Once the dataflows and workflows were in place, TheChemLabs used Astera’s job scheduler to set the frequency for each workflow. This helped them cut down manual work and accelerate the time-to-insights.
In addition to scheduling jobs, TheChemLabs set up triggers in workflows so that whenever a dataflow did not run successfully, an email with the error logs were sent so they could be rectified as soon as possible.
Start Cloud Data Integration with Astera
Many businesses may have the same cloud data integration need as TheChemLabs. Whether it involves cloud to cloud integration or between cloud and on-premise systems, Astera Centerprise can help automate the process and cut down both cost and time for the company. Furthermore, the built-in cloud connectors to cloud databases like Azure SQL, Google Cloud SQL, Amazon RDS, Oracle Cloud Database etc. allow more ease for users.
The 14-day free trial of Astera Centerprise allows you to explore the features of the product. Test out the built-in transformations, connect with various cloud sources, check errors with data validation checks and more. Get started today!