Navigating Cloud Migration Challenges for Data Warehousing

Challenges of Data Warehouse Migration to Cloud  

Data Integration Process 

Migrating data into a cloud-based solution involves significant effort to consolidate and synchronize different formats and types of data with multiple purposes and from various sources and applications, such as customer relationship management systems and enterprise resource planning. 

It also involves moving from an ETL to an ELT process. As data transformation is performed after loading the data into the target system in ELT, this can lead to a complex data transformation process. This makes it more challenging to analyze and transform a high volume of data as it is already loaded. Thus, you must ensure that you have chosen a robust and scalable infrastructure to handle large data volumes. 

But big data is not the only consideration. A lack of data quality can also substantially impact the success of the migration process, as it requires considerable effort and investment in data cleaning and data enriching. Again, since data is loaded before transformation in ELT, any data quality issues can be detected only after the data has been loaded. Therefore, data quality checks should be implemented at different stages of the ELT process to avoid errors. 

Resource and Cost Management 

Cloud-based solutions are generally more cost effective than traditional infrastructure, due to reduced hardware and maintenance costs, as well as the ability to pay only for the resources that are being used. However, the data migration process can be more costly than expected in terms of time and money when it is not based on a solid strategy.  

Indeed, inadequate research and planning, for example about the cloud provider and its data policies, can result in unexpected bills or fees. Ideally, the whole process should be completed in multiple stages, with extensive testing and validation between each of these stages. This requires significant technical expertise and investment in new skills for loading large amounts of data into the target system.  

Unfortunately, companies often lack the expertise and resources necessary to fully exploit new technologies autonomously. This is where Korem’s managed services come in handy, as it would allow you to outsource the management of your operations to our team of highly qualified experts. 

Data Security and Privacy 

Cloud providers typically implement various security measures, such as encryption, role-based access controls, and regular audits. This ensures optimal data protection, privacy, and compliance with regulatory requirements, and protects customer data and infrastructure from cyber-attacks and other threats. Moreover, cloud services often offer built-in disaster recovery solutions, allowing organizations to quickly recover their data and applications in the event of an outage.  

However, you must ensure that the security protocols provided by your chosen cloud provider meet your data security and privacy requirements. This is even more true for public cloud deployments, where an organization shares servers and infrastructures with other cloud clients. In this context, server vulnerabilities could lead to data leaks or other security incidents. 

In addition, you may not have visibility into where your data and applications are actually hosted in public cloud deployments, which can be problematic for certain data privacy laws such as the GDPR. For example, personally identifiable information (PII), personal data, or sensitive data will likely not be authorized for transit to external data platforms. 

According to a SANS survey, 56% of respondents are incredibly bothered about security as one of the major cloud migration challenges. Hence, data governance becomes essential to implement stringent security measures to ensure that data is secure, organized, and managed effectively, and that each user has access to the right level of data. 

Fortunately, through our contract management offer and licensing compliance support, we can help you better understand the terms and conditions (T&Cs) associated with each dataset and, if necessary, negotiate new T&Cs with your chosen provider. 

Data Visualization Tools 

Lastly, if you want to take full advantage of your data to answer business questions and solve geospatial problems, you must ensure that you choose the right visualization tool. Since visualizing massive amounts of data requires specialized tools and methodologies, your previous visualization solution may no longer be suitable for your needs.  

For example, with the CARTO Platform, you can quickly create intuitive location intelligence applications or use an application template to accelerate your geospatial analysis. It is also compatible with the leading cloud data platforms and analytics tools, such as Google BigQuery, Snowflake, Amazon Redshift, and Databricks. Learn more about geospatial technology taking on cloud-native platforms. 

Is Your Cloud Solution Right for You? 

When properly leveraged, cloud solutions can reduce costs, improve data accuracy and security, offer scalability, and provide business insights for data-driven decisions. But before choosing a cloud data warehouse, you should always ask yourself these few questions: