The benefits of data modernization: Why it matters

Data is said to be “the new currency”. But often data infrastructures are running on old, inefficient technologies. This makes it hard for organizations to find, trust and unlock the value of their data.

Today’s organizations require an adaptive data architecture using the latest technologies. These new architectures make it easier to democratize data across the organization and use it to drive business outcomes. This is often described as data modernization.

What is data modernization?

Data modernization is the process organizations go through to make their data easier to manage, access and activate. It means making their systems and processes more agile and scalable.

This includes moving their data infrastructure to the cloud so they can take advantage of the latest data technologies (data warehouse, data lake, etc.). As well as, updating their approach to data management including the tools, processes and people that are engaged. The end goal is to enable their organizations to quickly make data-driven decisions and drive more revenue.

Why is data modernization important?

Modernizing your data infrastructure helps you keep pace with current digital demands and create a foundation for business competitiveness in the future.

As data volumes grow and supporting technologies evolve, organizations must consider how they manage, access, store and even trust their data. Legacy systems can limit your ability to rely on data, reducing agility or slowing innovation.

Reasons to invest in data modernization include:

• Improved scalability and performance: Cloud data transformation, modern data architectures and better support for AI and analytics can help you move the needle for key performance indicators such as operational efficiency
• Faster decision-making: Access to trustworthy, real-time data helps employees at all levels make faster, more intelligent business decisions
• Better data security and compliance: Governance frameworks help enhance regulatory compliance and data safety, creating a shield against legal risks
• Improved user experiences: When you trust your data, you can rely on it for automated systems such as self-serve customer portals, creating efficiencies that better serve your clients and employees.

What are the benefits of data modernization?

Data monetization and data products are key drivers for data modernization and digital transformation. Organizations can increase revenue as well as customer and employee loyalty by using the data they have to do things like:

• Get closer to their customers and employees by personalizing the experiences they have with them. For example, customizing views based on user profiles and preferences. They can also use data to enable a better support experience and power a recommendations engine.
• Build products that customers want by customizing the product experiences to the user and their specific needs. Additionally, they can use data to inform product strategies.
• Drive employee satisfaction by gathering and using data to understand employee sentiment and addressing areas of improvement.
• Monetize their data by selling the data, metadata, and customer data that they have as a product. This enables them to expand their portfolio and increase revenue potential.

Data modernization is the driver for digital transformation. It’s what allows organizations to use their data to drive revenue and loyalty. Organizations that are always looking for innovative ways to use their data are those who tend to be the market leaders in their sectors.

What are the components of data modernization?

Comprehensive data modernization combines people, processes and technologies to transform how businesses collect, manage and use data. The major components of these processes are governance, integration and quality management.

Data governance

Governance offers structure to ensure data is managed effectively across your business. By using data governance tools and frameworks, you can define data ownership, apply policies consistently across functions and workflows and support accountability at every level of your organization.

Data governance is essential in creating reliable, secure data platforms that meet modern business needs while supporting compliance with growing external regulations and expectations.

Data integration

Data integration is the act of putting data to work in your native business software programs and other tools. Without integration, data is a liability without any ability to convert it into an asset.

Data quality management

Quality management is a foundational element of effective data transformation. As you import, export or otherwise move data, ensuring you end up with a clean, functional data set is critical to supporting operations. Modern data transformation systems help you transfer, cleanse, monitor and use data in a way that reduces rework and supports optimal insights for business decision-making.

How to implement a data modernization process

Data modernization is a journey. It consists of various initiatives that organizations will focus on over time. These include:

• Adaptive data and analytics governance: Building trust in their data with better governance. Allowing their teams to quickly discover, understand, trust and access the data they need.
• Expediting cloud data migration: Accelerating and reducing risk of their cloud migrations. Ensuring they only move clean, accurate and relevant data.
• Enabling enterprise-scale data quality: Integrating predictive data quality into their governance programs, while also improving data quality efforts with out-of-the-box rules and customizable workflows.
• Powering trusted, self-service analytics: Empowering business analysts and data consumers with accurate, complete and clean data for analytics.
• Streamlining trusted business reporting: Centralizing, governing and certifying key business metrics and reports. This helps to accelerate decision making and drive their business forward.
• Optimizing data lake productivity and access: Ensuring that data is easy to find, understand, trust and is compliantly accessible. Helping organizations get more value from data lake investments.
• Enabling your data marketplace: Making data, reports, APIs and models easily discoverable through a marketplace so employees can “shop” for the data they need, boosting productivity.
• Streamlining compliance management: Tackling today’s critical regulations including DCPR, CCPA, BCBS 239, CCAR, DFAST and Solvency II with a holistic approach to data privacy and governance.

To get ahead of the competition, enterprises need to turn their data into their company’s strongest asset. To do this, they must have a modern data approach that is flexible, agile and scalable. No matter where they start on their data modernization journey, the potential for increased revenue and improved loyalty outcomes are worth the trip.

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  Collibra

  Collibra

  Unified governance for data and AI