Migrating sensitive content securely: A guide for businesses | 2) Planning for a secure data migration

Welcome to the second part in our series of articles on the topic of data migration. In case you missed part 1, you can find it here.

In this second part, we will go through the stage of planing a secure data migration.

Identifying data for migration

The first step in planning a secure data migration is to assess the data you intend to transfer. This involves a detailed examination of your data. Identifying the most critical datasets that require immediate attention and prioritizing them is essential. This ensures that the most important data receives the highest level of security and protection during the migration process.

It is also crucial to consider data retention policies. These policies define how long specific types of data should be retained and when they can be deleted. By adhering to these policies, you can ensure that only relevant and necessary data is migrated, minimizing the risk of transferring unnecessary or outdated information.

Another important aspect of data identification is determining the necessary data cleansing and transformation processes. Data cleansing involves removing inconsistencies, errors, or duplicates from the datasets, ensuring the migrated data is accurate and reliable. Data transformation, on the other hand, involves converting the data into a format compatible with the destination system. This step is vital for ensuring seamless integration and optimal performance of the migrated data.

Establishing Migration Objectives

During the planning stage, it is essential to establish clear migration goals that align with your objectives. These goals act as a roadmap for the data migration project, providing clear direction throughout the process.

One primary goal of a data migration project is to ensure the timely transfer of data. Setting specific migration timelines helps prevent the process from dragging on for an indefinite period. By defining precise timelines, you can allocate resources and monitor the project’s progress.

Ensuring data accuracy is another critical objective. The migrated data must be accurate, complete, and consistent with the original datasets. This forces thorough validation and verification processes to identify and correct any errors that may arise during the migration.

Minimizing disruption to business operations is also crucial. It is important to reduce downtime or interruptions during the data transfer. By prioritizing this objective, you can develop strategies to mitigate risks and ensure a smooth transition.

Overall, setting clear migration goals is fundamental for the success of the data migration project.

Texport – Alfresco Exports & Imports

Introducing?a new mindset for upgrades and content transfer, we’ve developed a solution that exports and imports at object level supporting all Alfresco object types and it carries the symbology of true export.

• Full Support - Supports content, metadata, relationships, permissions, versions, tags, categories, sites-memberships and all other repository node relations from a source Alfresco repository to any target Alfresco instance.
• Optimized - Multi-threaded tool that leverages low level OS and cloud resources via it’s close relation with Python, as such it’s fully optimized for export/import throughput, ingestion rates of up to 2800 nodes/sec
• Native S3 - Native S3 support allowing full repository bidirectional transfer from a normal fileContentStore into an S3ContentStore
• Clean Data - Move all content or choose to archive or dispose certain areas of the repository – for example the archiving part of the audit-trail to increase database performance.
• Record - Keep a record of all exports and imports executed for validation and data quality purposes. It ships with an ElasticShearch integration providing robust dashboards in Kibana for content transfer executions overview
• Cloud Ready - Container friendly and Cloud ready, adding security and backup options in future relations.

A clever digital transformation…

Texport provides the opportunity to implement a clever digital transformation to the way the organisation interacts with their digital content, consolidating and enriching data – tagging, categorising, auto-classification, applying AI – thus increasing efficiency and optimising the investment.

TML – Texter Machine Learning by Texter Blue

Your content and data are the foundation upon which your business operates, and critical decisions are made. Recents advancements in AI in areas such as image and natural language processing have enabled a whole new level of automatic extraction of information and data analysis that power the automation of key business processes not possible until now.

• Process your data with different AI engines, integrating the results.
• Supports several data formats: images, video, text, etc.
• Generate new content and document versions based on AI results
• Store extracted information in metadata, enabling further processing and process automation.
• On cloud or on-premises – in case you don’t want data to leave your private infrastructure
• Compatible with several different ECM providers
• Ability to develop custom AI models to target your specific needs and data

AI is essential to remain relevant!

The adoption of AI in modern organisations is essential?to remain relevant and competitive, optimising efficiency, empowering new business opportunities and freeing critical human resources to specific value-added tasks.

If you’re struggling with your digital transformation, remember… you are not alone in this… Texter Blue is here to help you providing the best results! Make sure you read our news and articles and contact us.