We are all aware that data is at the heart of every business. In the past two decades, companies that have been most successful, are the ones who have been harnessing their data most effectively. The current global pandemic has highly accelerated the use of technology in businesses. Companies that harness emerging technologies like AI, ML, IoT, etc. backed by data will be able to provide better and innovative customer service and surpass others to become incredibly successful over the next decade and beyond.
Data is increasingly going to be generated at multiple touchpoints across the world. The growing adoption of technology by masses will bring about a proliferation of devices and platforms. Hence, we can safely predict that about 50 – 60% of the data generated by any organization will actually reside outside their data centers.
Data is useful only when it is extracted and passed on to business decision-makers in a timely manner. To achieve that the data needs to be passed on to the relevant technicians to actually gain a competitive advantage to accelerate businesses and make sure the data is extremely agile. To do this, organizations face multiple challenges like:
- Accessing data generated across varying formats and different locations
- Discovery of the relevant data
- Huge magnitude of data sets
- Managing the data
Businesses would also need to control the data and there would be an increasing oversight in terms of corporate governance, security, and regulatory compliance requirements. So, there are a whole bunch of operational, technical as well as business challenges that should be solved before data can be put to effective use.
Another interesting phenomenon is that businesses are going to put more and more of their workloads on the cloud, especially public clouds. Businesses will quite possibly have data in their own data centers and across public clouds. This will give rise to a new set of requirements:
- Movement of data across Public Clouds, Hybrid Clouds and on-premise Data Centers
- Operational ease while using multiple cloud solutions
- Controlling and securing the data
- Data back-up and restoration
Moreover, data generation is set to increase exponentially and as the data estate grows businesses will need to effectively optimize the cost irrespective of where the data sits, whether it’s across clouds or on-premise.
A possible solution to all these challenges is taking the help of a service provider that can offer an architecture that delivers simplicity to an incredibly complex data management solution. A solution that is extremely scalable, secure, and simple to operate. The different aspects of the solution should include:
- Thorough understanding of where the data is being generated – different applications and systems
- Monitoring the services that are effectively leveraging this data
- Controlling the data by integrating and extracting it from multiple sources
- Enabling advanced automation
- Helps overcoming operational challenges
- Effective data protection
- Constant optimization to enable effective response
About the author
Krithiwas Neelkantan, is the Director, Cloud Biz, NetApp, Bangalore. NetApp offers hybrid cloud data services for the management of applications and data across cloud and on-premises environments.