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Data modernization: a data leader’s answer to driving valuable business outcomes

Modern times call for modern data architectures. Legacy systems can’t keep up with the deluge of information being created by a world of connected people and things, nor with the increasing demands that data is placing on companies.

Keeping step requires that businesses move their data from on-premises legacy systems to the cloud, where they can unlock their data to do analytics, AI, and machine learning (ML) to anticipate market changes and improve business outcomes. Migrating data to the cloud is the first step. To derive true business value, data leaders need to develop modern data strategies in the cloud.

Data modernization is a shift away from legacy data technologies to more advanced and capable data platforms that enable AI, ML, faster decision making, more flexible and elastic storage-and-compute power, and, ultimately, more opportunities to unlock value from data. Data modernization is being driven not just by the connected digital age, but by the rise of the cloud for storing and processing data and the modernization of data platforms, capabilities, and tools for business applications.

This article lays out the fundamentals of data modernization and shows how companies are leveraging it to drive business value and gain a competitive edge.

Facing the data behemoth

Many challenges exist with large-scale data modernization. For example, there are insufficient budgets, limited in-house expertise, organizational and cultural barriers, and a lack of consensus among decision leaders.

Then, there’s the data itself:

  • Data volume comprises over 80 percent of all unstructured enterprise data that goes unused and is growing 55 percent to 65 percent per year.
  • 2.5 quintillion bytes of data are being created daily; by 2025, 73.1 zettabytes are estimated to come from IoT devices alone.
  • Data activity from active data lakes perform 100,000-plus events per second at peak levels; edge platforms processing IoT data can exceed that number, threatening to disrupt business operations.
  • Data is often siloed across multiple locations, and unforeseen issues such as inaccurate data can arise.

What may seem grim doesn’t have to be. The upside is that more data leaders are adopting a digital mindset and understanding the importance that data modernization plays in staying competitive.

Future-proof your data platform

The amount of data that’s here today and is looming on the horizon is staggering. So, the question every data leader should be asking is, “Can my data infrastructure keep up?” The answer is: It can with the right approach.

A data modernization platform should accommodate current and new workloads, as well as new technologies, capabilities, and features — today, tomorrow, and even months from now — easily and cost-effectively. Regardless of where you are in your data modernization journey, the following key pillars (from our partner Insight) will help you establish a successful data modernization initiative:

Make data accessible (and secure) so that stakeholders across the business can make informed, fact-based decisions.

Develop mature platforms that enable growth, innovation (AI, advanced analytics), operational efficiency, cost-effective scalability, performance-on-demand, and extensibility.

Establish governance for information protection, management, and integrity of corporate data.

Ensure security for the digital protections for all data, the physical security of that data, business processes that prevent unauthorized disclosure, and incident response measures.

Payoffs of data modernization at scale

Every data leader’s digital initiative should address data activation. Data activation is the concept of making every data point inherently useful and unleashing data’s value in real time and at scale. By unlocking your business-critical data, your company can extract the full business value from the modern cloud infrastructure to:

Run advanced analytics. Leverage advanced AI and ML capabilities available in the cloud for deeper, real-time customer insights that accelerate business value and outcomes, and generate new streams of revenue.

Become more flexible. Utilize cloud elasticity to handle your largest AI and ML workloads, as well as easily scale the systems up or down as needed so that you pay only for the data resources used.

Save millions of dollars. Eliminate both costly CapEx and the expense of managing complex on-premises infrastructures by moving to an OpEx model and cloud-managed services. Your data activation strategy will then pay for itself because you’ll be able to decommission expensive on-premises data centers, as a leading telco found.

Successful data activation, however, relies heavily on having a cloud-based modern data platform — one built on tools that enable your organization both to migrate your data efficiently, quickly, and at scale and store your data in one place, where it’s accessible to multiple users and for multiple business functions.

Modern data for the modern world, and the modern CDO

The role of the chief data officer (CDO) clearly has evolved since first appearing in the early 2000s, when the focus was on data governance and compliance. In more recent years, the CDO’s focus has been on using data to drive business outcomes, and the CDO has been instrumental in shifting their organization from legacy data systems to modern ones. And while some companies have not eliminated their older data warehouses altogether, their cloud-based initiatives are seeing the light of day.

A healthy dose of data-driven insights

An example of the benefits of data modernization comes from our partner Snowflake and Prisma Health. Prisma wanted to leverage its data from multiple sources to deliver better patient care to at-risk populations. When the volume of data sources grew too large, Prisma moved to the Snowflake Data Cloud because its legacy systems couldn’t keep up with unifying and making sense of all that data. By modernizing on Snowflake, Prisma 1) delivers an analytics-based COVID-19 vaccine program to patients and 2) gets results of the data that’s collected 10 times faster for half the price and pays only for the compute resources it uses.

A data modernization platform should accommodate current and new workloads, as well as new technologies, capabilities, and features — today, tomorrow, and even months from now — easily and cost-effectively.

Innovative data leaders are embracing data modernization, ML, and AI in the cloud. Developing the right strategy and choosing the right tools and partners will enable your live, business-critical data to flow freely — even during large-scale migrations — and will prepare you to build a modern platform that can harness the power of your information to deliver superior, customer-centric data experiences that, in return, offer valuable, actionable insights, to which your company can respond in real time to the needs of a dynamic business environment.

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