Traditional Data warehousing has hit a roadblock. Most organizations have ancient information management systems typically built in an age where inflexible systems working within solos were sufficient to address data needs of that era- limited data sources, infrequent changes, lesser volume of transactions and low competition. But today, the same systems have been rendered ineffective with the splurge in data sources as well as volumes. What’s more is that today, to remain competitive in a fast changing landscape, access to near real-time or instantaneous insights from data is necessary. Simply put, the legacy warehouse was not designed for the volume, velocity, and variety of data and analytics demanded by the modern enterprise.
Below, we have tried to capture in a nutshell how the modern or cloud data warehouse differs from traditional one.
| Traditional Data Warehouse | Modern Data Warehouse |
| Not designed for the volume, velocity, and variety of data and analytics | Designed for sheer volume and pace of data. |
| Accessible only to the largest and most sophisticated global enterprises | Can be used by individual departments like marketing, finance, development, and sales at organizations of all types and size |
| Prohibitively expensive and inflexible | Affordable to small and mid-sized organizations, very easy to adapt dynamic changes in data volume and analytics workloads |
| Slow batch processing, crippled business intelligence | Data available immediately and at every step of modification, supporting data exploration, business intelligence and reporting |
| Inability to handle growing numbers of users | No limitations on number of users |
| Updated analytics on a weekly or daily basis and no accessibility easily | Data insights can be always up to date and directly accessible to everyone who needs them |
| More focus on data management | Empowers enterprises to shift their focus from systems management to analysis. |
| Limitations of an approach and architecture where changes are infrequent and carefully controlled | Operates painlessly at any scale and makes it possible to combine diverse data, both structured and semi-structured |
The emergence of cloud has been monumental in modernizing the data warehouse. Cloud data warehousing is a cost-effective way for companies to take advantage of the latest technology and architecture without the huge upfront cost to purchase, install, and configure the required hardware, software, and infrastructure.
To conclude, on-premises workloads will continue to shift to the cloud. In the days to come, the cloud data warehouse will replace the on-premises warehouse as the main source of decision support and business analytics. Azure SQL Data Warehouse, a cloud based data warehouse hosted on Microsoft Azure is capable of processing massive volumes of data and can provide your business the speed & scale that it needs to manage enterprise data.
At CloudMoyo, we help you migrate your data platform to the Azure cloud, as well as help build customized solutions in Azure to make the most out of your data. To know more, book a 5-day Azure Assessment workshop to jointly build the strategy and roadmap to move to a cloud-based data deployment.
