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The Main Challenges in Data Migration and How to Effectively Overcome Them

01 Aug 2023

Every year, information-intensive businesses spend billions of dollars just to migrate the data. Yet, most of the new systems do not live up to expectations, typically because migration errors lead to partially validated data.

Due to the view that the system itself is an investment, any data migration effort is often perceived as an unavoidable and expensive affair. This results in an overly simplistic, underfunded approach. However, migrating to a new system as part of investment offers the business better access to accurate data that supports its needs and helps to reduce the risk of delays, scope reductions, and budget overruns. 

The global Cloud Data Migration market is predicted to grow at a CAGR of nearly 30% from 2021 to 2030. Therefore, every business must value information as an asset and employ data analytics to gain a competitive edge. 

Why is Data Migration Important? 

It is usually necessary to migrate data when switching to a new system.

For example, relocating or consolidating an application may be required to replace a legacy application or deploy a new application alongside another application.

The goal of data migration is to improve performance and gain a competitive advantage, regardless of its specific domain. Having accurate data can maximize the value of an enterprise application.

However, migrating existing data to a new application can introduce inaccuracies, redundant and duplicate information. The data in the source system may be inadequate to meet the requirements of the target system, both in terms of content and structure. Safety is another concern when it comes to data transfer. Unsafe data transfers will amplify errors or irrelevant information, perpetuate hidden problems, and put you at risk.

  1. Cloud computing and multi-cloud technologies.
  2. Use of A.I. Technology for data-driven business culture.
  3. Shift to the Data Analytics approach of decision making.
  4. Use of Data Fabric system for reducing data disparity.
  5. Use of Blockchain technology for centralized data management.
  6. Introduction to edge computing for real-time data analytics.
  7. The shift from big data to granular data to perform analysis and make intelligent business decisions.

Related Article: Data Quality Management: Benefits of Electronic Document Management System Every Business Owner Should Know

Do you know?

A study by IDC in 2021 found that almost 82% of businesses now use multiple cloud technologies or plan to do so within a year.

Critical Challenges of Data Migration 

  • Availability of data in an unorganized state

Data may have multiple versions when it is first created from scratch. Messes typically arise from duplicates of a document or a file or incomplete data sets of a document or a file.  

Before moving to a new platform, you should clean this data so that it won’t be messy or disorganized right from the start. With a knowledge management system powered by Artificial Intelligence, data in this scenario can be deduped after migration to reduce costs. 

  • Inadequate data protection

A common concern during data migration is data loss. Data loss is inevitable during data transfer, primarily at the organization level. It is difficult to rely on new content right away because of data loss. Losing data can be highly disturbing However, data loss can be negligible when it comes to junk files or duplicates of files, which are no longer needed.

However, organizational data may contain confidential or private information despite being inconvenient to daily operations. Therefore, to ensure that there is no data loss, you should have a backup of all files, irrespective of whether they are essential or not. 

  • Incorrectly formatted data

The organization’s data and the compatibility of files are to be checked during data migration. It is essential to format documents before just transferring them, as they must be opened in a format that works with the new software on the server or the device.  

A file may not be compatible or have access controls if it has not been formatted before it is transferred. By inspecting the device’s current settings and the operating system used in the extension, you can ensure files are appropriately formatted. Before moving, you must decide which changes the files need to make to work on the new server or software.

  • Analyzing and mapping data 

When new data is transferred from the old database, mapping refers to determining where the new data goes. The main objective is to decide where to store the data in the new database.  

Turning a manual knowledge management system to one that is more efficient, a critical step is for the workflow to adjust due to the ease-of-use features within the knowledge base software. It might be complex, but your knowledge management partners need to specify how you might simplify the process.

  • Bringing data into the system

Data has been cleaned, formatted, and mapped; now, the information must be imported to the new platform. As a result, you have better search capabilities, a more cohesive interface, and better data organization when you move to a new knowledge base platform.  

This is only possible when you import data correctly. It may be necessary to move all information tables at once to improve search results. Currently, organizations should spend more money to ensure the successful use of the new knowledge base features in the long run. These measures will allow them to expand their business.

  • Lack of collaboration among teams

Data migrations do not require the same technology, different people, and in some cases, a mix of internal employees and contractors. Some of these employees might even be in other locations. Working in silos and creating more data silos can lead to inconsistencies and decrease productivity.

It is more common for people to avoid responsibility when things go wrong rather than taking action to resolve the issues. Collaboration tools help with migrations by enabling all participants to view data in the same way as it moves through the stages, thus preventing mistakes and misunderstandings.

  • There is no integration of processes

There are typically multiple people and technologies involved in data migration. Data and its design will not be transferred smoothly between the analysis, development, testing, and implementation stages if disparate technologies are used. Information may be lost during the transition. To reduce error rates and save time and money, organizations should consider implementing a platform that combines each stage’s critical inputs and outputs.

  • Finding the Right Experts

Data migration activity is crucial since businesses drive maximum value from the data collected over the years. If you do not have the right experts to do the migration job for you, you will likely put your data at risk. Make sure you get the right people on board to perform the data migration safely.

In data migration, you face challenges and high risks. Still, if you identify these hurdles early and overcome them before any data is transferred or transformed, you will have a successful migration.  

Else, you can hire a team of experts to manage your data migration. One of the reliable recommendations for successful data migration is Qualityze. They have a dedicated team of experts who understand its value to your organization.

Qualityze provides next-generation quality management solutions for businesses that strive for quality, safety, reliability, and compliance. They ensure your transition to a new quality management system is smooth with their exceptional data migration services. The entire range of smarter quality solutions is made configurable to suit your growing business requirements. Are you ready to experience the Qualityze difference for excellence yet?

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For more concerns and queries, please get in touch with our customer success team at, or you can give us a call on 1-877-207-8616, and we will be right there for you.



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