In the world of data-driven decision-making, mistakes are going to happen. Even the best data systems will have errors sometimes. The most important is how those errors are handled. To get the most out of data, organizations need a solid way to deal with errors.
Defining error handling
Error handling involves implementing processes to detect and solve errors, ensuring a smooth process. Whether transitioning from older systems or working in a cloud environment, error handling identifies issues within datasets and addresses them before they causa an impact. These errors are often related to data quality, such as missing fields, duplicate entries, default values, incorrect formats, and human errors.
Why is it important?
If any errors slip through during data transfer, data will end up being of low quality. Having a good error handling system helps with catching mistakes that might otherwise go unnoticed and allows for the handling of bigger amounts of data.
Dealing with errors manually is hard work. For example, if there are addresses in the wrong format, checking each one by hand takes a lot of time. Fixing mistakes later can be costly and mess up data analysis if bad data gets through.
Automated error handling
Automated error handling takes care of data quality issues like completeness, timeliness, and validity automatically, without needing any manual work. It can quickly check and validate data as it comes in, following specific rules set beforehand.
4 benefits of automated error handling
Automated error handling brings several benefits:
1) Reduced manual workload
Automation simplifies validation tasks, making them faster and more efficient compared to manual methods of error detection.
2) Empowering teams
User-friendly interfaces enable non-technical team members to participate in data validation, enhancing collaboration and decision-making.
3) Real-time quality checks
Data is assessed against predefined standards and rules in real-time, ensuring accuracy and integrity without delays.
4) Enhancing trust
Reliable data increases confidence, leading to better-informed decisions.
Texport: Alfresco Exports & Imports by Texter Blue
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 its 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.
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TML: Texter Machine Learning by Texter Blue
Your content and data are the foundation upon which your business operates, and critical decisions are made. Recent 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.
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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.