Graduate from enterprise to ecosystem data for holistic analytics
The increasingly digitalized world we live in results in the creation of more and more data. While most companies focus on collecting, integrating, and analyzing their enterprise data, the most innovative companies think about data in a much more holistic and broad sense.
In one dimension, the innovators think about all sources of data and include competition, regulators and influencers in their data universe. In a second dimension, they think about data that is generated outside of the walls of the enterprise - including that of customers, employees, partners and suppliers. Finally, they think about all forms of data: structured, unstructured, alphanumeric, text, sentiment, and emotions.
The insights of innovators who are thinking ‘ecosystem data’ are far more complete, current, and accurate. This, in turn, leads managers at all levels to make the right decisions.
Shift to cloud: Analyze data holistically and accelerate digital transformation
The trouble is that traditional ERP, CRM, HRMS, service management or even custom applications are neither designed to capture such data, nor are they scalable in on-prem environments for running analytics.
Cloud solutions provide several advantages over local data warehouse appliance setups. The move from on-premise data warehousing into cloud or cloud data-lakes offers several benefits:
Storage and Processing Scalability
Ecosystem data can run into petabytes, and a significant drawback for on-premise data warehouses is limited computing capabilities, which are essential for large scale data. Every time an on-prem server reaches maximum capacity, companies must upgrade or add capacity, resulting in processing downtime.
Cloud platforms offer virtually infinite scalability via pooled computing resources. You can quickly provision more vCPU, RAM, or storage capacity when needed, and this allows for continuous analysis of very large volumes of data.
Modern cloud hosting platforms use resource-based billing models to minimize operating costs. This means that when you move to the cloud, you will only pay for the computing resources you use, saving money in the long-term. Depending on the platform you choose, you also have access to a range of storage options, including SSD, HDD, and tape-based storage drives, allowing you to minimize costs when storing infrequently accessed datasets.
Along with resource-based billing, cloud platforms also take away the burden of infrastructure maintenance, freeing up IT staff hours to work on development rather than repetitive infrastructure management tasks. This translates to indirect cost-savings, as human resources are utilized more efficiently when compared to an on-premise data warehousing approach.
Cloud Disaster Recovery
On-premise data backups can be time-consuming and challenging to automate, especially with traditional data warehousing solutions. Monumental amounts of hard drive space are needed to facilitate backups in the first place, leading to increased hardware costs.
All major cloud platforms have built-in disaster recovery functionality, offering backup replication and scheduled backups that help you achieve recovery point objectives (RPOs) and recovery time objectives (RTOs). For older backups, you can transfer them to slower (read: often lower cost) archive storage solutions in the cloud, further reducing your disaster recovery operation costs. You can even leverage the power of third-party multi-cloud replication-as-a-service tools to increase network resiliency further.