Top 5 Data Migration Trends for 2022 | SpringTimeSoftware

Data migration trends reflect pain points and opportunities in data management. In our modern, data-driven economy, data managers face the challenges of rapidly growing data repositories and the need to replace legacy data storage solutions. These challenges force data migration to new solutions capable of handling more data.

Meanwhile, the value of data mining demands data scientists' ever-increasing access to data, as well as the ability to examine data in detail to extract deeper insights. The types of data also change as the Internet of Things (IoT) includes new sources such as video, audio, and sensor data.

Some older solutions that may have additional data capacity will not be able to handle new data sources. This inconsistency provides another force for the adoption of data migration tools.

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5 Trends in Data Migration

Companies progress at different rates and will migrate for different reasons. The five key trends in data migration reflect the widespread recognition of the benefits of data migration to solve specific problems.

1. Continuous change in cloud

Given the universal increase in the amount of data, large enterprises quickly exhaust the capacity of local hard drive arrays. Data managers struggle to avert the constant demands of excess capacity and stay ahead of hardware obsolescence and failure.

Migrating data to the cloud will not completely eliminate these issues, but they do reduce the urgency and complexity. A mouse click on the cloud interface easily replaces the hours of installation, configuration, testing, and troubleshooting required to install a physical hard drive. The ease and potential automation of scaling storage provides a strong appeal for data managers and drives the trend to move more and more data to the cloud.

The largest companies continue to exceed their current capacity and markets and markets expect these large enterprises to continue to dominate the demand for data migration in dollar terms. However, small and medium-sized enterprises are expected to drive the fastest-growing segment of the data migration market as the flexibility of the cloud becomes more widely recognized in 2022.

2. Data-Driven Migration

Data migration has been around as long as we've had data, and our data should remain intact even if the media fails. Whether our modern data manager is moving data from local data centers to the cloud or between cloud resources, data managers want to improve cost, performance and accessibility with their next solution.

However, as managers change their data, effective data managers also want to move the right data to the right place. Rather than massively rebuilding their existing data storage solutions, data managers are now looking to transform data into more usable configurations.

This transition serves higher goals than simple storage. Data managers want to improve analytics, integration with other systems, and more. For example, instead of replicating local storage for 20 subsidiary offices, an enterprise can create a global repository by data classification: global marketing, operations records, logistics records, security log files, etc.

To improve data usage, data managers will perform data migration to specific tools or locations for specific subcategories of data.

3. Surging Unstructured Data Migration

Data analysis is only used to work on structured data. Now, with the continuous improvement of the processing power of cloud resources and the advantage of artificial intelligence (AI), unstructured data can be incorporated into various types of data analysis.

Unstructured data simply means files or data outside the database. The data can be as small and easy to process as a text file or as complex and cumbersome as a video file containing multilingual audio content.

With increasing computing power, IoT video feeds, spreadsheets, presentations, PDF invoices, and many other files can now be included in our analysis and provide new insights to data scientists. However, in order to do so, these files must be accessible to the analysis tool. This is increasing the demand to move old and new unstructured data to new data repositories for analysis.

4. Shifting Demand Markets

Markets that already recognize the value of data migration, such as the banking, financial services, and insurance (BFSI) industries, are predicted to continue to use data migration heavily. Similarly, marketing departments across industries are expected to maintain their position as market leaders in adopting and using data migration to improve their data analysis capabilities.

However, as the understanding of data migration benefits expands, the fastest growth now comes from new industries and roles. The market and market expect HR to be a segment that grows rapidly as HR executives look for data migration to consolidate multiple data sources for better data analysis.

Similarly, retail and consumer goods are the industries that are expected to show the highest growth as they seek to improve their understanding of customers throughout the product and customer life cycle.

We can expect this shifting demand between industries and job functions to continue as the advantages of data migration and data analysis become more widely understood. While we may not be able to predict next year's fastest-growing segment, we can certainly expect a sustained turnaround.

5. Data Modernization

While previous data migrations may have moved data from one repository to another, data analysis improves efficiency and effectiveness when the AI ​​doesn't need to waste cycles trying to figure out what's in the data. This need drives data modernization, which includes moving data migration from legacy databases to modern databases.

By using data modernization, unstructured data gets classified and structured, and old databases get restructured and refined. In a recent Deloitte survey, 84% of respondents have begun the process of data modernization with the BFSI industry leading the demand.

Companies that did the first data migration to the cloud have now become active participants in data migration related to data modernization. This helps established industries maintain themselves as leaders in the data migration market.

For example, marketing departments may have been the first to migrate data to the cloud to perform data analysis, but they now offer scalability, cost reduction, flexibility, performance, and expanded functionality.