“The ability to imagine and generate new ideas with speed and to implement them through global collaboration is the most important competitive advantage.”
—Thomas Friedman, The World Is Flat

Globalization has leveled the playing field. Threats to your business are no longer constrained by distance or geography. Leading companies see the cloud as a key to competitive advantage. Today, enterprises are moving many legacy applications to the cloud to support Friedman’s vision of global collaboration. Many orgs are migrating to the cloud for scalability, agility, speed and flexibility. In the cloud, enterprises can drive agile and quick decisions — and compete more effectively.

Yet to realize this vision, people need access to data. Data producers and consumers alike are working from home and hybrid locations more often. And in an increasingly remote workforce, people need to access data systems easily to do their jobs. This might mean that they’re accessing a database from a smartphone, computer, or tablet.

Today, data dwells everywhere. Data modernization enables informed decision making by pulling data out of systems more reliably. It helps you identify high-value data combinations and integrations. It also helps people rapidly identify opportunities in the moment — so they can take advantage of something that might have otherwise have been missed, and ultimately generate more revenue.

Further, data modernization reduces data security and privacy compliance risks. Its process includes identifying sensitive information so you can limit users’ access to data precisely and efficiently.

McKinsey & Company’s bar graph demonstrating companies aim to shift the majority of their IT-hosting spend to the cloud.
McKinsey found that the pandemic accelerated cloud migration and spending.

What Is Data Modernization?

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration.

So what’s the appeal of this new infrastructure? Modern data architectures, like cloud data warehouses and cloud data lakes, empower more people to leverage analytics for insights more efficiently. With the right data governance strategy and data democratization measures in place, more people can self-serve curated, trusted data — scaling data-driven decision making across the business.

A data modernization strategy helps you create data management and data governance practices that optimize intelligence tools while enhancing data privacy and security across all cloud, multi-cloud, and hybrid IT environments.

What Is the Role of the Cloud in Data Modernization?

Using cloud-based data platforms gives you the ability to extract more value from your data. With cloud architecture, you’re able to leverage:

Elasticity

Adapt to demand, and provision or cancel resources as needed to save costs.

Capacity

Access the resources your data applications need — no more, no less.

Data Pipeline Automation

Consolidate all data sources to automate pipelines for processing in a single repository.

Advanced Tooling

Access the latest tools without purchasing additional licenses.

Data modernization optimizes your cloud data platform capabilities by standardizing your data types and tags to efficiently use and monetize your data.

What Are the Benefits of Data Modernization?

Too often, companies have siloed data across legacy solutions, applications, cloud-based systems, and data stores. To realize the value of your data, you need to integrate and combine data sources in new and creative ways. Only then can you extract insights across fragmented data architecture.

A broken and siloed data estate thwarts analytics projects. In this kind of environment, analytics tools won’t be able to provide the insights that you need. Data modernization gives you a way to develop systems and processes to generate revenue. Here are some of the benefits that data modernization has across business operations:

1. Efficient Data Processing

To use data, you need the ability to collect and correlate it efficiently. Data modernization reduces the time it takes data users to find high-value data and analyze events. Your data modernization plan should empower business users with a way to connect and recommend data sources to one another.

2. Enhanced Accessibility

In a “work from anywhere” world, people need to access data from wherever they are, including from home. Data modernization improves visibility into sensitive data so you can limit access without blocking people from doing their jobs.

3. Stable Business Growth

Data modernization creates standardized processes across shared data, applications, and technologies. By creating a common language around data, you have a reliable ecosystem of data and insights that grows with your business.

4. Improved Decision-Making

When people have real-time access to data, they can make faster, more informed decisions in the moment. Data modernization allows you to grant access appropriately for data democratization, where people enjoy a self-service analytics environment that allows them to collaborate, innovate, and share knowledge.

5. Use of Reliable Databases

Consolidating all data across your organization builds trust in the data. By improving data quality, you can build scalable and adaptable processes that cut costs and boost margins.

Healthcare and manufacturing are among the top industries leveraging data modernization to take advantage of these benefits.

McKinsey & Company’s graph showing how cloud-based vertical application are a major draw.Healthcare and manufacturing are projected to double their public-cloud spend (McKinsey).

What Is the Role of Data Governance in Data Modernization?

Data governance is the cornerstone of data modernization. At every touchpoint in the data modernization process, you need to know what you have, how it’s classified, and who should access it.

For example, as you build out your data modernization initiative you need to consider:

  • Before Migration: What data is popular? Active data governance uses AI and ML to identify your most used (and useful) assets so you can prioritize migration accordingly.
  • During Migration: Lineage with impact analysis helps you identify assets with on-premises dependencies to prevent downtime during migration. In addition, data governance gives you visibility into private or sensitive data that needs additional security protocols.
  • After Migration: Cloud data governance helps you set the appropriate access controls to establish and maintain a robust compliance posture.

How to Modernize Data with Alation

Data migration is like moving homes. You must know what you have, organize, and decide what to move, and what to leave behind. You must move, unpack, and reorganize in a new environment – clearly communicating where things live to the other residents. Data modernization helps you manage this process intelligently. Optimizing the cost of cloud services is the key to extracting the most value from your data and technology investments.

Alation helps data analysts modernize their data so they can migrate what’s most important and extract value. Our platform helps you take a consumer-centric approach to data management by using intelligence and automation to ensure efficiency. With Alation, companies can lay a trusted foundation that powers hybrid IT and multi-cloud infrastructures, eliminating data silos that lead to inefficient data use. To learn more, request a free demo to see how Alation can help you modernize your data through cloud data migration.

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