Data Migration

What is Frictionless Data Migration?

Before exploring some of the common risks and benefits associated with data migration, let’s start with establishing first what migration is and how enterprises might use it.

What is data migration?

A data migration is the process of moving data from one system to another. More complex than data replication and integrations, this critical initiative can generate long-term value for businesses. When not done right, however, migrations can introduce unnecessary risk, time, costs, and potential failure.

Tyler Warden, Senior Vice President of Products and Engineering at Syniti, explains, “A common misconception is that data migration is just about moving data from one place to another. To provide real value, you need to move the data that matters to your business in a way that matters.”

Data Migration Use Cases

  1. Enterprise Resource Planning (ERP) consolidation

Legacy, on-premises ERP systems quickly balloon into a sprawling ecosystem as the organization adds and modifies functions like payroll. Using data migration to transition to the newest version of an ERP or consolidate multiple systems helps confidently plan for disaster recovery and continuity of services.

  1. Mergers & Acquisitions (M&A)

Combining data across multiple companies after an acquisition or merger is a complex undertaking. Even when businesses have similar infrastructures, their configuration and usage of data objects vary. Systems likely exist in siloes throughout the organization. The required data isn’t readily available and often needs to be constructed. Inattention to proper data profiling, mapping, or archiving puts data migration budgets and timelines at high risk, as well as the value of the M&A.

  1. SAP® Migrations

Data migration is one of the key processes in an SAP implementation. Whether implementing SAP Central Finance, S/4HANA, or Ariba, transferring data to an SAP environment modernizes the IT infrastructure and increases business agility. Adopting SAP solutions like SAP S/4HANA requires conversion to Business Partner to consolidate Vendors, Customers, Suppliers, etc., but requires the right technology and strategy to deduplicate and harmonize this critical master data.

  1. Moving to the Cloud

Whether it be migrating global HR solutions or moving procurement or PLM solutions to a SaaS platform, businesses looking to modernize their infrastructure use data migration for replacing systems with cloud-based data solutions or migrating an existing one into a cloud environment. Moving to the cloud can simplify data processing and storage but creates new data management challenges. Have a plan of attack ready to avoid common cloud migration challenges.

What are the types of data migration?

There are many approaches to data migration, but most migration strategies can be lumped under two categories: incremental and batch.

  1. “Lift and Shift”

A “lift and shift” approach to migration is done when data is transferred with very minimal changes to your data, typically in a one-off, batch process. This type of data migration frequently leans on Extract/Transform/Load (ETL) to process and transition data to new databases. For most enterprises, ETL is not enough to deliver a successful migration as systems experience extra downtime and corrupted, unmanaged data.

  1. Incremental

Incremental data migrations, sometimes referred to as trickle migrations, complete the migration process in phases in order to eliminate downtime or operational interruptions.

Compared to other approaches to migrations, incremental implementations can be complex. However, the added complexity — if done right — reduces risks and delivers long-term value. Methodologies like Syniti’s eight-step migration, for example, make sure only the most relevant, up-to-date data is moved in a safe and purpose-driven manner.

Access Syniti’s 8-Step Data Migration Methodology Manual

Data Migration Risks & Mistakes

Data migration can be risky business. Whether you’re migrating to a new ERP or CRM, or modernizing your infrastructure to the cloud, transferring data is no simple task. For a successful migration, do the necessary preparation work and be aware of the most common migration risks and mistakes.

  1. Security

Any time legacy applications and systems are shut down, decommissioned, or migrated, data security is put at risk. Enterprise application data is susceptible to unauthorized access or tampering to maintain privacy and data integrity.

Transparently remove risks by securing application data access without impact to existing applications using data encryption and client authentication to protect sensitive data. If not properly done, however, migrating encrypted databases can cause data corruption or data loss.

  1. Data loss

The impact of lost or transposed data is arguably one of the most detrimental risks to a poorly planned migration. Migration approaches like ETL have no built-in data quality checks and no visibility, putting entire enterprises at risk when it comes to compliance, privacy concerns, and of course, failed migrations.

  1. Extensive project timelines

Waiting until after Go Live to identify and correct data issues leads to unplanned downtime that has costly, downstream repercussions on stakeholders, IT and data scientists, customers, and more. As a result, costs increase because other teams can’t do their jobs with other projects still underway.

  1. Excess costs

Increased costs of a data migration can be both direct (how much services cost) and indirect (lost revenue, unplanned downtime, etc.). As risks increase, project timelines expand and services spending explodes. Standing costs increase because other teams can’t do their jobs with other tasks still underway. The risk of complete failure of the migration as well as complete loss of the business value is exponentiated.

Benefits of Data Migration

Often thought of as a risky undertaking, data migrations actually serve many valuable benefits to the business when executed strategically.

  1. Minimize redundant data

A common way of creating redundant data is when transferring information from one database to another, whether that be by replication, integrations, or migrations. When done right, however, a migration project can actually reduce irrelevant, duplicate data and database size. Move only the data you need by archiving and deduplicating data ahead of a migration. By loading & testing with real data early, the entire migration project can be de-risked, even long after Go Live.

  1. Reduce data storage costs

Data migrations give organizations a chance to decommission legacy systems and remove extra operational costs from environments that IT is responsible for. By taking advantage of a migration to evaluate the integrity of existing data – what's needed, what’s duplicated, what’s outdated, what’s improperly mapped or profiled – stakeholders can optimize or reduce total spending on software, services, and maintenance contracts.

  1. Improved data security

Data migrations can give organizations the opportunity to increase the level of quality controls and visibility to their data. This means more secure data via limiting unauthorized access and ensuring data is properly backed up to prevent data loss. A cloud-based migration solution can provide extra controls and enable automatic data quality checks and deduplication before Go Live, ensuring only the most trusted data is migrated.

  1. Upgrade to new technology

Organizations should take full advantage of migrations to modernize infrastructures, data warehouses, or optimize analytics. This might mean taking advantage of cloud data platforms or updating to new database systems entirely.

Best Practices for a Frictionless Data Migration

New approaches to cloud-based data management platforms contain migration best practices like autogenerated code and intelligent metadata scanning readily available to generate value well beyond Go Live.

  • More intelligent code auto-generation: Writing more code better helps reduce technical code development by up to 80%, freeing up resources to work on higher-value tasks.
  • Higher quality data can be delivered faster in the migration: Intelligent matching and harmonization with more than 99% accuracy.
  • Pre-loaded best practice content: Including mappings, designs, and rules to help accelerate migrations.
  • Intelligent metadata scanning and profiling: Active metadata scanning helps identify and correct data errors, with analysis to identify, action, and resolve data anomalies; helping to accelerate processes and enhance analytics functions.

Data Migration Tools

Chief Technology Officer at Syniti, Rex Ahlstrom, advises, “Data Migration is an overloaded term that means different things to different stakeholders. Don’t make the mistake of lumping all data migration vendors and technologies together or you may risk data migration failure.” A data migration solution that captures the knowledge gained so it can be used for all data initiatives moving forward turns an otherwise complex project into a competitive advantage.

With data tools to streamline every step of the data migration process, including Data Catalog and Governance, Replication, and Data Quality, Syniti Knowledge Platform delivers faster, frictionless enterprise data migration from one trusted cloud data platform.

Going to a new application, be it ERP, CRM, SRM, or any other should not be thought about as the end of a journey but rather the beginning of a journey to a higher value of data for the enterprise. Missed opportunities to remove legacy systems, improve data quality, and ensure complete tracking and visibility of data causes your new environment to quickly atrophy, increasing data management costs in the long run.

Want a deeper dive into how to deliver a frictionless data migration every time? Sign up for our on-demand webinar here.

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