Modernizing Data Storage for fuelling Digital Transformation

Reading Time: 5 minutes

As companies mature in their digital transformation journey, old technologies and rules of doing business are being re-defined. Capturing customers is no longer enough and companies are focusing on how to keep them engaged with hyper-personalized experiences. There’s an explosion of data sources as everyone and everything is connected with mobile devices, social media, and IoT

What this means for a business is an exponential increase in the speed & volumes of data that needs to be handled and the necessity for this data to be available at all times, under all conditions. Because of this phenomenon, the demand for modern data centers has increased to support better agility, high-performance, and sophisticated service delivery. 

Data is no longer highly structured information from a limited number of data sources. The reality that business leaders face today is the fact that data comes in several types and is much more complicated to handle coming in from multiple sources. The real challenge is making this data relevant for the tech leaders, CXOs and the Line-of-business so that they can derive meaningful & transformative insights. 

So, how are organizations responding to these data challenges? We will be exploring this in detail further. 

What are the drivers for this change in Data Storage Infrastructure?

Before we explore this topic in detail, let us first understand what we exactly mean by data modernization. It’s simply the transition from legacy data infrastructures to modern ones owing to changing data requirements.

With huge amounts of unstructured data like images, audio, social media comments, clinical notes in health care, modernizing the data infrastructure has become ever more critical. 

The industry is taking data modernization seriously

Deloitte conducted a survey of 504 IT companies in the United States and here are a few findings –

Businesses are now digitally driven

As per IDC, there will be a stark growth in the number of “digitally determined” organizations that are fully equipped with an integrated enterprise-wide tech architecture solution. This number has grown from 46%  to 90% and has been cultivated by digitally-driven businesses that are becoming more focussed on their messaging and adding richer experiences into the customers’ portfolio.

Innovation has presented new challenges

Innovation is being fuelled by the app revolution with next-generation cloud-native apps. Intelligent applications, digital platforms, and technologies are taking care of customer needs round the clock. The crux is that organizations are investing in terms of people, process & technology when it comes to digital transformation.

But one major challenge that arises is the silos in organizations in terms of innovation. What we mean is that innovation is happening in different layers in the organization, for instance, chatbots in the frontend and inventory management in the backend. The problem is, connecting the dots and finding a common ground for all the individual infrastructures that power these different layers of innovation.

The single enterprise strategy

The process begins with a single enterprise strategy that lays the foundation for a long term investment strategy. The objective is to power technological innovation with a fully integrated organization-wide tech architecture while modernizing the internal IT environment.

This organization-wide tech architecture is fuelled by a modern data & storage infrastructure. Data is absorbed by organizations from all sources – internal & external, processes, API based data streams and more. The idea is to make this data available for insight and transformation so that it can be converted into timely action before the value of the data expires. 

How can organizations modernize their data storage to empower Digital Experience (DX)?

Let’s dive deeper into how enterprise architects and CIOs can modernize their data management & infrastructure to overcome the challenges that modern organizations are facing.

Hybrid Cloud Infrastructure as Code

Most organizations use a combination of multiple cloud infrastructures. Business leaders get to exploit the advantages of traditional data centers as well as public & private cloud architectures. A truly hybrid cloud architecture will help you in the following.

Efficient and flexible delivery of resources across clouds – Data becomes available across and can be utilized for multiple use cases. The hybrid cloud allows the use of a public cloud for backups, recovery, and data retention.

Administer Infrastructure as a Code – Enterprises can deliver public and private cloud infrastructure as a shared reservoir of software-defined resources made available with APIs. These resources can be smoothly integrated with DevOps or as a part of the business process.

Address governance & security-related concerns – Integrates your organization’s modern cloud infrastructure & traditional data centers to a common governance and security system.

Embrace AI for data management solutions

Organizations are turning to AI for data-driven insights to derive new business opportunities for products or markets, empowering salespeople to have a meaningful sales pitch, and improving internal processes. 

AI and ML-enabled solutions directly enhance the performance of data management, which has a transformative impact throughout a business. For instance, Machine Learning has the ability to define new paths a query can take and thus speed up the process. The use of natural language querying can go a long way in helping LOB users employ Internet-like- search to draw valuable inferences on time. 

“88% of the business leaders from the companies surveyed said that AI and ML are indispensable to their data platform & analytics initiative.” – IBM Research Report

Minimize the total cost of your ownership

To manage your organization’s financial resources well, CIOs have to ensure that their database solutions must optimize the costs while maintaining industry standards and adhering to Service Level Agreements (SLAs). Data management costs can be contained by –


A range of administrative tasks like setup & deployment, workload management, resource utilization and storage management, along with maintenance, upgrades, and capacity expansion can be automated so that the focus shifts more towards strategic initiatives. Choosing data solutions with on-premise and cloud architectures sharing a common codebase can help save time and effort on rewrites.

Optimize the storage requirement

A large chunk of the IT budget is spent on storage requirements in the form of hardware, hosted & cloud services, and managed services. But the storage requirement can be reduced significantly using techniques like data compression and multi-temperature data management capabilities which have a direct impact on storage requirements. Cluster topology transparency is another efficient way to reduce storage requirements as applications are unaware of the fundamental cluster & database deployment thus speeding up coding & testing.

Ensure security threats are at bay

Security and IT professionals should be ready with answers to some difficult questions like –

  • How can we be prepared for malicious attacks anytime, anywhere?
  • What types of access control techniques are being deployed? Will they be able to battle emerging threats?
  • What steps are you taking to protect internal & external data?
  • Are our server and storage defence frameworks imparting all-inclusive, end-to-end coverage—both on-premises and in virtualized environments?

Cyber-resilient architecture is your key to unlock the security concerns of your application.  

A cyber-resilient architecture is designed to safeguard servers, whether they are traditional data centres, remote storage, and as part of software-defined data center. Under the purview of cyber resilience, all the issues before, during, and after a threat or an unforeseen event are taken care of by IT leaders. 

Is data modernization on your mind?

Organizations often struggle with the growing volume, variety, and velocity of the data, decisions inspired by data, automating business processes with cutting edge technologies. In this scenario, it becomes necessary to master data engineering to ensure that the right infrastructure is in place to operationalize data pipelines required to perform analytics on growing volumes of data. 

Through our comprehensive analytical knowledge and expertise, we embed data and intelligence into our clients’ business processes to deliver data solutions that unlock new revenue growth and cost efficiencies at unprecedented agility and scale.

Knoldus can help you revamp your data infrastructure to enable it to fuel your modern requirements. Get in touch with us to schedule a call with our expert or drop us a line at

Written by 

Niharika has around 3+ years of experience as a Content Professional. She loves writing about technology and the latest trends in the online world although her rich writing experience spans across diverse business domains. Apart from writing, she has also worked on YouTube audience growth strategies. An ambivert by nature, she likes to grab a snack with a warm cup of coffee accompanied by a good book or a close friend.