An Overview Impact 

Integrating cloud data warehousing with business intelligence can result in improved decision-making, increased operational efficiency, better understanding of customer behaviour, and enhanced competitive advantage.

This is why we are not only building on the foundational understanding of data warehousing as caption in our previous article (Data warehousing wonders: a leverage for business value in 2024) but also exploring the cutting-edge advancements and practical applications of its cloud-based solutions, making it highly relevant for businesses looking to maximize their data-driven decision-making capabilities in 2025.

What is Cloud Data Warehouse?

Databases hosted on the cloud is referred to as cloud data warehouse.

Data warehousing and cloud data warehousing share the fundamental goal of storing and analyzing large volumes of data.

It can integrate data from various sources, including structured and unstructured data, for the purpose of reporting and analyzing.

One of its major advantage over the on-premise data warehousing is that it can be accessed anywhere its users resides provided there is Internet Connection

However, cloud data warehousing differs significantly over traditional data warehousing. Here are seven major concepts:

7 Basic Concepts of Migrating into Cloud Storage

It is important you know that we are focusing more on the “how modern cloud-based data warehousing solutions are transforming the landscape of business intelligence (BI) and analytics”, providing organizations with –

1. Greater Flexibility: Adapt to changing business needs without a need for significant capital investment
2. Scalability: Based on the amount of data and the number of queries, it can scale up and down
3. Performance: It provide high-performance query execution and data processing
4. Storage: Storage of cloud data is in highly durable manner that accommodate different access pattern
5. Data Integration: On-premise databases allows the ingestion of data, IoT devices and third-party applications into cloud storage with 100% safety.
6. Reduced Maintenance: The cloud provider handles infrastructure maintenance, updates, and scaling.
7. Advanced Features: Access to advanced analytics, machine learning, and artificial intelligence tools.

The above concepts form the foundation of cloud data warehousing, enabling organizations to leverage their data more effectively and efficiently.

Top 4 Cloud Data-Warehousing Providers in 2025

Cloud providers handle maintenance, upgrades, and security, reducing the burden on in-house IT teams.

1. Amazon Redshift: A fast, fully managed data warehouse service that makes it simple and cost-effective to analyze all your data using standard SQL and existing business intelligence tools.
2. Google BigQuery: A fully managed, serverless data warehouse that enables super-fast SQL queries using the processing power of Google’s infrastructure.
3. Microsoft Azure Synapse Analytics: An analytics service that brings together big data and data warehousing.
4. Snowflake: A cloud-based data warehousing company that offers a fully managed service with separate storage and compute, enabling independent scaling.

Use Cases of Cloud Warehouse of all time

• Business Intelligence and Reporting: Aggregating data from various sources for comprehensive reporting and analysis.
• Customer Analytics: Analyzing customer behavior to improve marketing strategies and customer satisfaction.
• Financial Analysis: Conducting financial analysis and forecasting to support business decisions.
• IoT Data Processing: Ingesting and analyzing data from IoT devices for real-time insights and monitoring. 

Now, let’s try to consider some advantages which guarantee more insight of cloud data warehousing solutions as against traditional data warehousing with the followings

1. On-premise infrastructure/cloud-based infrastructure

On-Premise: deployed using an organization’s own hardware/software infrastructure with a fixed capacity, based on the physical hardware resources available.

Cloud-based are hosted on cloud platforms provided by vendors and offer scalable capacity, adjust resources dynamically based on current demands.

2. Fixed Capacity/Scalable Capacity

On-Premise: Needs additional hardware that is time consuming/expensive. They are static in nature with difficulty in achieving urgent data-volume expansion

Cloud-based: It can scale resources up and down to meet changing demands, workload but ensuring optimal performance and cost efficiency.

3. Fixed cost/Variable cost

On-premise: Cost are fixed with its usage notwithstanding, therefore incurring more expenses based on proposed needs.

Cloud-based: A pay as you go model of resources engaged. Cost reduction is possible during scale down of resources.

4. In-house management/Vendor’s management

On-premise is not cost effective thereby, in-house IT teams is needed to manage resources, backups and eradicate security breach. 

Cloud-based: Maintenance, updates, Security is sorely handled by cloud providers with less burdens on the IT teams.

5. Limited accessibility/Global accessibility:

On-premise: Data access is limited due to Organization’s local networks which cannot be used remotely. Integration of data from multiple sources is almost impossible.

Cloud-based: Working remotely is 100% possible from anywhere globally with access to internet connection.

Compatibility and Security 

Data is replicated across multiple regions thereby provide high availability and reduce the risk of data loss.

Also, the cloud providers offer automated backup and disaster recovery solutions which ensure data quick restoration in the event of a failure.

Again, structured and unstructured data are offered scalable storage solutions for easy storage and management of large dataset.

Here is what to expect when you migrate from Traditional Data warehousing into Cloud Data warehousing.

1. Seamless Integration: Cloud solutions offer robust data integration services that can easily ingest and process data from various sources, including structured, semi-structured, and unstructured data.
2. Data Protection: Cloud platforms implement robust security measures, including encryption, access controls, and auditing, to protect sensitive data.