Most businesses are having difficulty implementing the new technologies that have emerged at the platform level in the last five years. We should be concerned about data warehousing’s “now” and how to leverage the new technologies to build your company’s “future.”
New methods and technologies efficiently eliminate limitations, making the future flexible and open to the most daring and innovative businesses. The future lies in how each business makes the most of new methods and tools to deliver exceptional client experiences. A pause to allow the sector to process the new capabilities would be beneficial.
What is a Cloud Data Warehouse?
The fact that a cloud-based data warehouse and its on-premise counterparts share many features and functionalities should come as no surprise, but there are a few crucial differences that significantly affect everything from capabilities to operations.
Updating software is a significant issue with on-premise data warehouses, which you will no longer have to worry about if you switch to a cloud-based EDW. Updating software has the advantage of delivering new and interesting features regularly, such as integrated machine learning assistance or sophisticated geographic information systems (GIS).
Cloud databases are an example of a scalable platform that can expand to accommodate your company’s need to employ more data for decision-making. Cloud databases are arguably the only option if you want to successfully implement large-scale analytics in a potentially economical manner. Cost-effective is the crucial word in the preceding sentence. Paying for resources used is a constant cost of adopting a cloud data warehouse, and this directly corresponds to your capacity and desire to use a greater range and depth of data. A consumption-driven cost model will be exchanged for software licensing and data engineering costs. Conciliating that can be challenging.
What Do Clients Want from Data Warehousing?
Having access to all your data through a single service is a major trend in data. Large-scale serverless data warehouse systems, such as Google’s BigQuery, may store and serve an enterprise’s data needs as a single endpoint if you can get your data into a single store. You must investigate the next wave of emerging data virtualization technologies that can present a single data service view into multiple data warehouses, whether on-premises, in the cloud, or any combination of the two.
Reducing the amount of data engineering and operations needed for traditional data warehousing is another popular approach. A serverless paradigm reduces or does away with the demand for a data engineering/ operations team because the cloud provider handles the scaling and uptime requirements.
In conclusion, the capability of the upcoming generation of data warehousing supports:
- A single gateway to all your data
- Access control and governance based on policies
- Interfaces with high UX discoverability
- caters to all customer needs, including those involving data science, machine learning, and business intelligence
Cloud Warehouse Benefits
Data Access: The capacity to store a wide variety of data types, along with the inherent flexibility of cloud services is a consequence of large scalability. This enables a very wide rollout of data services without worrying about the capital and human resources scaling needs. We cannot underestimate this freedom from traditional friction points when the goal is to enable as many people as possible to access resources. Nothing quashes momentum more than needing to hire more data engineering personnel or acquire additional hardware.
Performance and Scalability: Without a doubt, traditional on-premises data warehouses are scalable. The liberation from DBAs and DataOps is the true innovation. Even in smaller quantities, your organization will need these people.
Newer Technologies: Traditionally associated with data lakes, these features are increasingly seen in cloud databases, particularly in the fields of machine learning and data science. Certain Vendors have taken a more assertive stance in attracting such workloads and offering natural support. Innovation should be anticipated to continue beyond the conventional definition of warehouses.
Some Challenges Associated with Cloud Warehouses
Security Risks: This is entirely mechanical, and there are no architectural flaws. Data must be relocated, and new protection must be put in place for it. Applications that produce data must be redirected, and the infrastructure that stores data must be adjusted.
Cost: Cost can be a concern. Vendors can sometimes try to sell whatever they can, and you must be aware of what broad adoption will cost you.
Performance: Achieving a good performance at times can be sometimes challenging. It will be good if data warehouse and virtualization vendors continue to work their performance roadmaps in perpetuality.
Conclusion
As of now, there isn’t a competitive on-premises option for what cloud warehouses offer. The use of cloud data warehousing solutions by organizations is driven by such factors as operational simplification, performance, security, and agility. While lock-in is an issue, if you can consolidate all your data into one large warehouse, do it. The benefits of doing so are immeasurable. You may also consider using virtualization technologies to establish a single data warehouse consumption endpoint.
Read Whitepaper Cloud Data Warehouse: Exploring Self-Optimized Technologies