Jul 5th, 2024

Achieving Digital Success Through Data Modernization

Author - GuruPrasad Murthy
Achieving Digital Success Through Data Modernization
Jul 5th, 2024

Achieving Digital Success Through Data Modernization

In today’s data-driven landscape, clean, well-formatted, easy-to-access data is crucial to making informed decisions when it comes to strategy, scaling and marketing. Data modernization is crucial for addressing the challenges businesses encounter in managing their data. Unfortunately, many businesses face challenges when it comes to managing their data. Legacy systems are prevalent, and moving away from them when your company’s processes are deeply entrenched in them is difficult.

Today, we’ll explore data modernization: what it is, why it’s important for your business, and what steps you can take toward modernizing your data and moving away from clunky legacy systems. We’ll also talk about some of the potential pitfalls of modernization and what to watch out for when implementing your own legacy app modernization initiative.

What is Data Modernization?

Data modernization refers to the process of updating a business’s data management systems to bring it up to par with the rigorous data requirements of modern industry. Specifically, it means updating the infrastructure—both physical and code-based, practices, security, analytical tools, and processes by which a company manages data.

Benefits of Data Modernization in Business Growth
  • Leveraging data is essential for making informed, intelligent business decisions.
  • Without data, you cannot identify who your customers are, their needs, where they live, how they act online, or how to tailor your product to meet those needs.
  • Modernizing your data infrastructure leads to better insights into consumer behavior.
  • It allows your company to operate more efficiently by removing pain points that may cause blockages for engineers and analysts.
  • Data modernization improves security and alleviates privacy concerns.
  • It makes your software more flexible and scalable.
  • It makes data more accessible to people at all levels of your organization.
What are the steps for modernizing data?

When planning your data modernization initiative, it’s important to plan extensively and employ a multi-pronged approach.

1. Assessment

Your data assessment should be a rigorous audit of all your current systems and processes, as well as the primary stakeholders for those systems. Ensure that you discuss the desired outcomes and potential pitfalls of the migration with anyone who will be affected by the changes. Run through all potentially affected parts of your codebase to ensure backwards compatibility.

Next, make a backup of all your data. This is perhaps the most important step of any data modernization effort. Do not forget this step!

2. Pre-Migration Tasks

In this stage, you should clean and format your existing data. You might want to enlist the help of an outside service to help you do this, such as a data migration service or database performance tuning service. Classify, label and standardize all your existing data. Understand its shape and how it is used.

3. Transformation

Find any gaps in data that may need to be filled—you may want to fill these using data enhancement tools. This can include things like missing contact information, invalid emails addresses, improperly formatted phone numbers, etc.

Remove duplicate records and other inconsistencies. You should also understand how the data will need to change in order to fit into the new platform.

4. Migration

This is the stage at which you actually transfer data out of legacy systems and into new silos, databases, pipelines, etc. Make sure you have a robust, staggered plan with plenty of fallbacks and safety nets. Your existing services should not be affected by the migration, so make sure you can guarantee uptime while the migration is happening. You may need to duplicate data or route requests to temporary storage solution while the migration is underway.

5. Post-Migration

Establish monitoring and consider a DevOps strategy and planning meeting. Hook up any data visualization and reporting services that need to be in place. Compare new data instances to the old data to ensure that no inconsistencies have been introduced. You’ll also need to ensure that employees are properly onboarded and trained up on any new processes.

You may want to enlist the help of a software development partner who can implement database testing services and QA testing services for this stage.

What to watch out for when planning a data modernization initiative?

The primary thing to be cognizant of when planning a legacy app modernization is data loss. Data loss not only affects you, but can also negatively impact your clients and customers, particularly if there is also a security breach.

Additionally, it’s important to involve all stakeholders as early in the process as possible, and to establish metrics for success early on. Thoughtful planning and careful consideration of all parts of the system involved are paramount to ensuring a smooth and successful data migration.