Data warehouses are essential to every organization’s IT ecosystem in the modern world. They lay the foundation for numerous use cases that facilitate quicker decision-making and insights, such as dashboarding, business intelligence (BI) reporting, and machine learning (ML)-based predictive analytics. 

The emergence of cloud computing has enabled data warehouses to offer new features, including highly scalable computation and storage, pay-as-you-go pricing, fully managed service delivery, and affordable petabyte-scale data storage. Businesses are allocating more funds towards cloud applications. 

However, we have identified some common myths about cloud data warehousing that prevent businesses from embracing the cloud. 

Myth 1: Cloud Data Warehouses are Expensive 

Companies frequently experience shock, when considering migrating their data warehouses from on-premise to the cloud due to the total cost of ownership. Nevertheless, a more thorough examination is required to make an informed choice. Conventional on-premises warehouses come with added costs for managing the business infrastructure, a hefty initial capital investment, and regular support fees. Cloud Data warehouses, on the other hand, might have a higher yearly membership cost, but they already cover the initial outlay as well as ongoing costs. 

Customers can also benefit from elastic scalability, less expensive storage, lower maintenance and upgrade costs, and cost transparency with cloud warehouses, giving them more control over their warehousing expenses. Industry experts project that businesses that adopt best practices for cloud cost controls and cloud migration will save an average of 21% when they utilize public clouds. Additionally, they believe users of Hybrid clouds who go through end-to-end reinvention will achieve a 13% revenue growth rate. 

Myth 2: Cloud Data Warehouses Leave you with Less Deployment Control 

According to some DBAs, cloud data warehouses are less flexible and in control than on-premise data warehouses, which makes it more difficult to react to security risks, performance problems, or natural disasters. As on-premise warehouses, cloud data warehouses now offer the same level of control maturity. Numerous other features are also offered by cloud warehouses, including high availability, automated backup and restoration, failover to other data centers, and sophisticated security and alerting systems. 

Cloud Data Warehouses that accept new, open data formats are being used to classify, ingest, and query unstructured data types to promote the adoption of machine learning. This feature makes data easier to access by keeping it in an open format, giving data scientists more flexibility for data exploration and machine learning modeling, enabling governed data use of unstructured data, enhancing teamwork, and breaking down data silos with streamlined data lake integration. 

Furthermore, some DBAs are concerned that switching to the cloud will make their knowledge and abilities less necessary. In actuality, though, cloud data warehouses simply automate data warehousing’s operational administration, which includes stability, scaling, and backups. This leaves DBAs to focus on high-value jobs like performance optimization, warehouse architecture, and ecosystem connections. 

Myth 3: Cloud Data Warehouse Migration Must be Either 100% or 0%

Businesses migrating to the cloud frequently feel pressure to move everything there to justify the expense associated with it. Nonetheless, distinct deployment settings might suit various workloads better. By adopting a hybrid-cloud approach to data management, businesses can choose where to execute particular workloads while maintaining control over expenses and workload management. It enables businesses to benefit from the scalability and elasticity of the cloud while maintaining internal control and security over critical workloads. 

Myth 4: Regardless of the Vendors, all Data Warehouse Migrations are the Same 

CTOs frequently feel pressure to “modernize” and remodel their entire technological stack when shifting to the cloud, which includes selecting a new cloud data warehouse provider. Nonetheless, several iterations of data replication, query optimization, application re-architecture, and DBA and architect retaining are typically necessary for a successful move.  

Before thinking about switching to a new platform, enterprises should assess whether a hybrid-cloud version of their current data warehouse vendor can meet their use cases to reduce the complications. This strategy offers several advantages, including a more efficient transfer of data from on-premises to the cloud, a decrease in the need for query tuning, and continuity in automation and tools. Additionally, it helps businesses to build a decentralized hybrid-cloud data architecture in which workloads can be split across cloud and on-premises resources. 

Myth 5: On-premises Warehouses Offer Higher Levels of Security and Compliance than Cloud Data Warehouses

Businesses in highly regulated sectors like manufacturing, insurance, transportation, and finance must follow a complicated set of compliance regulations for their data. This requirement frequently adds another level of difficulty to the process of transferring data to the cloud. Companies also have intricate needs for data security. However, in the last ten years, cloud providers have faced a wide range of compliance and security requirements, including SOC2, PCI, HIPAA, and GDPR. The emergence of sovereign clouds and industry-specific clouds addresses governmental and industry-specific regulatory needs. Furthermore, warehouse providers assume the duty of patching and safeguarding the cloud data warehouse to guarantee that business users continue to adhere to rules as they change. 

Conclusion 

Organizations can make more informed decisions about their hybrid-cloud data warehousing strategy and realize the full value of their data by addressing these five common misconceptions about cloud data warehouses and learning about the subtleties, benefits, trade-offs, and total cost ownership of both delivery models. 

Read Whitepaper Cloud Data Warehouse: Exploring Self-Optimized Technologies