In today’s dynamic data-driven business world, the proliferation of data and the need for advanced data analysis have rendered Traditional Data Warehouses ineffective. Many organizations use Traditional Data Warehouses, which leverage on-premises infrastructure and require companies to manage the necessary hardware and systems. As they demand more time and effort from the companies, these traditional systems pose numerous challenges in meeting present-day expectations and demands.
In a survey comprising IT professionals conducted by a multinational technology company, 95% responded that managing a traditional data warehouse requires a lot of manual intervention.
As a solution to this problem, Cloud data warehouses came into existence. The data and IT leaders in numerous companies are increasingly taking the initiatives to invest in them because these data warehouses align well with their business requirements and help them unlock the full potential of data. They help companies uplift their business reputation and gain a competitive advantage.
This blog post provides an overview of Cloud data warehouses, explaining how they differ from Traditional Data Warehouses and the value they bring to businesses.
Table of Contents
What is a Cloud Data Warehouse?
In simple terms, a cloud data warehouse is a data warehouse deployed on the cloud, allowing organizations to focus more on making informed decisions based on the insights derived from the data rather than worrying about managing the underlying infrastructure. The improved access to data, enhanced data security, and scalability that a cloud data warehouse offers allows businesses to implement advanced data analytical processes while reducing IT costs and the total cost of ownership.
Difference between a Traditional Data Warehouse and a Cloud data warehouse
| Feature | Traditional Data Warehouse | Cloud Data Warehouse |
|---|---|---|
| Deployment Model | Deployed on-premises, necessitating manual infrastructure management. | Cloud-based in nature, but supports a hybrid approach as well (both on-premises and cloud). Eliminates the need for manually managing the infrastructure. |
| Data Sources | Data is gathered from limited sources such as operational databases, ERP systems, CRM software, etc. | Data is gathered from various sources, including social media, IoT devices, scanners, and others. |
| Scalability | Lack of scalability causes challenges in handling large and dynamic datasets. | High scalability, enabling effortless processing of huge volumes of data. |
| Ease of Configuration | Setting up a traditional data warehouse can be complex, time-consuming, and resource-intensive. | The configuration of a cloud data warehouse is relatively simple. |
| Integration with Third-party Tools and Analytical Capabilities | Traditional data warehouses struggle to integrate with third-party tools, making it challenging to perform advanced analytics. | Cloud data warehouses support advanced tools that enable predictive analytics, machine learning, and other such technologies. |
Moving to a Cloud data warehouse
The comparison between traditional data warehouses and cloud data warehouses reveals the reasons that compel companies to migrate to cloud data warehouses. However, the lack of expertise or direction often prevents organizations from tackling the complexities involved in this data modernization process and achieving successful outcomes.
If you’d like to learn more about how companies can migrate to a cloud data warehouse, head over to our blog post.
Explore how our end-to-end data warehouse consulting and implementation services can empower you to meet your unique business requirements.
How to Choose the Right Cloud Data Warehouse Solution
Choosing the right cloud data warehouse is important for organizations to maximize their ROI and reap the benefits. Several key factors need to be considered when choosing a cloud data warehouse, including:
1. Security
Security should be a top priority for businesses when selecting a cloud data warehouse. They should ensure that the cloud data warehouse offers robust security features and secure data transfer methods. The solution should enable businesses to effectively manage access controls, preventing unauthorized users from accessing the data.
2. Data Types
Businesses should be clear about the types of data they deal with. Some cloud data warehouses are known for effectively handling structured data while others are optimized for handling structured, semi-structured, and unstructured data. Also, it is essential to analyze the data formats that a data warehouse supports. Ideally, organizations should go for a cloud data warehouse that can gather various data types from disparate sources, including JSON, XML, etc.
3. Scalability
As businesses grow, it becomes important to have a cloud data warehouse that can handle increasing volumes of data while maintaining optimal performance. Enterprises must implement a cloud data warehouse that can efficiently scale vertically (enhancing the capabilities of a single server) and horizontally (adding more servers), enabling parallel processing of massive volumes of data. They should look for auto-scaling features that dynamically adjust resources when computing demands are high.
4. Integration
The chosen cloud data warehouse should integrate seamlessly with existing applications within the organization to ensure seamless data migration and effective data synchronization. The cloud data warehouse should support integration with popular business intelligence (BI) tools, such as Tableau, Power BI, and others, to streamline data visualization and analysis.
Are you ready to get started with a Cloud Data Warehouse and pave the way for a successful data-driven business?
Final Note:
Cloud data warehouses have become an integral part of businesses. According to Marketsandmarkets, the cloud data warehousing market is expected to reach a valuation of $12.9 billion by 2026. This reflects the increasing commitment of businesses to their digital transformation initiatives. Additionally, by partnering with a well-established IT partner, organizations can truly leverage the full potential of their cloud data warehouses.
As a trusted IT partner, KANINI helps businesses across various sectors optimize their digital transformation journeys by building advanced data systems. We strive to deliver exceptional value to our clients, enabling them to gain a competitive advantage. Reach out to us to learn more about our capabilities.
Author
Soundar Vetrivel
Soundar is a results-driven professional with 16+ years of diverse experience in Data Analytics and Project Management. Currently spearheading data warehouse projects at KANINI, Soundar is known for his forward-thinking approach, delivering value to our clients. His expertise extends to managing enterprise architecture processes, data management programs, and creating innovative business solutions powered by advanced analytics.
