Why is data modernization key to a winning data strategy?

With the world’s economies increasingly complex and interlaced, the amount of data generated, stored and used globally has increased exponentially, reaching a staggering 59 zettabytes in 2020. Therefore, adopting a modern data architecture that can cope with growing volumes of data is a competitive necessity for today’s businesses.

For most organizations, the evolution of data architecture it has been largely driven by changes in business and operational requirements. However, there are some key aspects of data modernization that are common to all companies. For example, the need to improve traditional use cases and make them more profitable. In addition, this new generation of data architecture is mainly based on some shared data management tools. These include classic data storage, data lake, and real-time streaming.

But whatever the industry or use case, the path to data architecture modernization involves revolutionizing data-centric technology. This includes migrating siled data from complex legacy databases to modern cloud-based data lakes to ensure agility, efficiency, and a fast ingestion process.

1. The need for a modernized data architecture

Before we delve into why companies need to modernize their data system, let’s briefly take a look at how legacy data management tools work. The traditional data stack involves a wide range of tools that must be perfectly aligned with each other to generate results. These systems had been designed to handle static and predictable data from a fixed source.

However, with the diversification of data sources, structured and unstructured, there has been an exponential increase in the unpredictability and complexity of data. This change made traditional data management tools complex, expensive, and unable to solve modern data problems. And the change has been rapid.

Today’s data and analytics platforms can help businesses build a flexible and scalable data stack. Data modernization facilitates productivity by revolutionizing the way companies collect, process, analyze and use data and make better business decisions quickly.

They provide a cohesive view of diverse data assets and a single point of access to your users while at the same time:

  • Improve data governance by ensuring compliance with privacy and data protection regulations
  • Ensure access to the right data at the right time
  • Break through organizational silos by gathering data from multiple points of origin
  • Provide actionable, insights that can meet the needs of a dynamic business environment.
  • Reduce costs, reduce data latency, speed time to market, and improve decision making
  • Accommodate unstructured data and open source technologies

Also from a data strategy perspective, data modernization can have significant benefits. By enabling the democratization of data across the enterprise in real time, a modernized data architecture can help derive strategies that support lower operating costs, improved data security and governance, and improved data quality.

Hybrid infrastructure: As business data continues to grow by leaps and bounds, companies must consciously develop robust data retention strategies and governance policies around that data. Most importantly, companies need to discover a workable data storage architecture, whether in multiple clouds or in a combination of on-premises and cloud data centers, to ensure optimal analytics delivery.

This makes data modernization an even more critical task. A modern business must systematically plan, upgrade, and build the right data storage architecture to modernize the data core.

Data from various countries: Another key factor for data modernization is the frequent change in regulatory requirements between countries surrounding data practices. Today, most companies do not have their operations restricted to a particular location or country.

The rise of offshoring and nearshoring business models has forced companies to extend the periphery of their own data across borders. And this has brought business data into the realm of diverse but strict data regulations.

In the US, for example, state and federal regulations for data retention range from 5 to 30 years. This depends on the type of data and the nature of the regulation. In such circumstances, companies that rely on inaccessible data formats can face significant hurdles in querying data, ultimately resulting in lost revenue and non-compliance.

Data usage monitoring: Cross-border operations also require multiple teams operating from different locations to evaluate the same data. To ensure seamless access to data, companies must thoroughly audit data usage and monitor resource utilization. This is another area where data modernization can make a difference by creating a data lineage, which maintains transparency by helping teams maintain a clear audit trail.

2. Impact of the cloud on data modernization

Cloud computing symbol on top of a tablet held in a palm

Image Credit: Sigmoiddotcom

When we talk about the contemporary IT landscape, we see two very dramatic changes. One of them is data modernization. The other is the rise of the cloud. And the convergence of the two has laid the foundation for recent developments in digital transformation.

Cloud data warehouses are the enabling factor for data modernization. According to a Deloitte survey, 55% of organizations see data modernization as a key component of cloud migration.

The cloud offers better performance at reasonable costs and ensures high scalability along with:

  • Improved capacity: Having a serverless infrastructure has its advantages. A fully managed cloud platform can help users scale seamlessly without having to worry about standard database operations.
  • Increased flexibility: Cloud platforms help automate the resource allocation process on demand. This ensures greater flexibility.
  • Better access to tools: Cloud platforms eliminate data silos and focus on providing a unified data view across all business functions
  • More in-depth information: Cloud computing automates data pipelines and unifies data sources in a single cloud repository. This allows for deeper, faster and better insights.
  • Better securityAnother critical aspect that makes the cloud an ideal launch pad for all data modernization initiatives is its state-of-the-art security management feature that is often designed to allow organizations to leverage cloud applications and networks through its full potential while mitigating potential threat vectors and security issues. For example, most cloud platforms come with encryption key management that helps businesses restrict data loss and ensure data integrity by encrypting mission-critical data and securing connections.
  • Enabling the architecture of transient and stateless applicationsFinally, the proliferation of the cloud has helped modern technology stacks become significantly modular. It provides an agile and flexible platform for transient and stateless application architectures to thrive. Stateless application architectures enable the seamless implementation of simpler and smaller microservices and help companies to leave behind the clunky monolithic applications of the past.

3. Key steps to modernize a legacy data system

You don’t need to take an all-or-nothing approach while modernizing your legacy data system. Businesses can remain competitive and relevant without building their data stacks from scratch. A well-designed hybrid system can solve many of the problems that legacy systems present.

Here are some steps to upgrade your legacy system distilled on this principle:

  • Evaluation: Start by defining your challenges, goals, and needs. Don’t get overwhelmed or overly excited about the complete overhaul of your systems. Instead, evaluate the new IT stack against its features, business value, and your customers’ willingness to embrace the change. Over time, you will be better positioned to decide whether you need a full transition or a hybrid adoption.
  • Migration: Even if you are not interested in completely replacing your existing IT stack, you should consider adopting the cloud. Migrate data to a cloud platform It frees you from technological limitations and can be a good step toward legacy modernization. You can research to understand which cloud tools are relevant and used by competitors in the market and then adopt them.
  • Adoption: Adopt containerized applications that separate infrastructures from applications. This will ensure flexibility and portability.
  • preparation: Be prepared for future growth and possible changes. This will help you stay relevant for a long time, even in the midst of dynamic market conditions. You can document the KPIs and benchmarks and create a plan for future updates to ensure the same.
  • Camaraderie: Choose the right technology partner based on your needs and budget. The ideal technology partner should integrate your legacy systems with a cloud infrastructure or replace them entirely if necessary.

Data is the core of modern-day businesses. As a result, business leaders can no longer ignore capabilities that can enhance the value of data. Data modernization is one of those evolutionary aspects of the data management solutions necessary for a company on an accelerated journey towards digital transformation.

Image credit: provided by the author; AdobeStock; Thanks!

Nitin kumar

Nitin kumar

Nitin is an Engineering Manager at Sigmoid and has a decade of experience working with Big Data technologies. He is passionate about solving business problems in the banking, CPG, retail, and QSR domains thanks to his expertise in cloud and open source technologies.


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