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Why data modernization matters By Terri Schlosser

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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…
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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 are companies taking advantage 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. 

How can organizations make it a reality?

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

Cataloging and governing data assets: 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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