All things data quality, our company blog

This blog is dedicated to all things data quality. We'll discuss why quality is critical for your business and how you can enhance it using automated tools. Learn from our experiences and make data quality your priority.


Data templates for a smoother regulatory ride?

In today's complex financial landscape, data exchange is crucial for transparency, efficiency, and compliance. FinDatEx, a standardization initiative, is streamlining data sharing among EU financial institutions. By adopting FinDatEx templates, firms can enhance data quality, reduce costs, and improve market efficiency.


Wrapping up compliance on document processing

As scrutiny in financial industries grows, Mesoica helpds firms automate evidence generation and integration into workflows. Resulting in the elimination of time-consuming secondary proofing processes and incomplete evidence. Efficiency, credibility, and compliance can be achieved by streamlining the creation of evidence as a logical byproduct of (partly) manual processes.


Mesoica's ISO 27001 Journey: Bolstering Trust, Simplifying Partnerships

Mesoica has achieved ISO 27001 compliance, solidifying our commitment to security and privacy. Following best practices, such as automated testing and software deployments, contributed to this achievement. ISO 27001 establishes our credibility and showcases our dedication to data security.


First time right: perfect document data quality

Manually validating document data is prone to errors and can lead to problems later in the process. In this post, we will discuss how Mesoica can help you automatically validate data in PDFs and other documents. We will emphasize the importance of automation and demonstrate how our data quality platform enables you to take action.


Turn documents into data

Mesoica revolutionizes document handling by automating text extraction, effortlessly extracting table data and smart entitiy matching. This transformative solution slashes manual work, reduces errors, creates a robust audit trail, and ensures 'first time right' accuracy, transforming documents into well-integrated parts of any data pipeline.


Simplify, organize, excel: Introducing our smart inbox

Simplify data handling, unlock automation, and reshape workflows. Seamlessly gather data from any source, reducing reliance on specialized knowledge and fostering a more efficient workplace. Embrace a new way of unstructured data management for a streamlined, stress-free workflow.

How to

Data Quality, Simplified: Mesoica's Integration with Azure Data Factory/Synapse Pipelines

This guide provides a step-by-step approach to seamlessly incorporate Mesoica's data quality platform into Azure Data Factory /Synapse pipelines, guaranteeing clean and reliable data throughout the entire process. Empower your team with user-friendly exposure to data quality, non-technical rule definition, and the simplicity of integration.


Maintaining data quality: 3 key actions to improve data pipelines

In the complex world of data management, maintaining data reliability is paramount. In our blog post, we explore the three fundamental actions required to keep your data pipelines on track. By setting clear boundaries, defining precise rules, and ensuring effective communication, you can navigate the data quality challenge and ensure that your data remains dependable and meaningful.


What we learned about data quality at the Big Data Expo

We've just wrapped up two days of insightful discussions at the Big Data Expo. In a nutshell: Few data quality vendors, lots of in-house solutions, and data quality remains an engineering focus. Dive into the full scoop below.


What to expect from Mesoica at the Big Data Expo

Facing challenges in manual unstructured data handling, quality monitoring, or compliance? Visit us at booth 174 at the Big Data Expo in Utrecht on September 12-13 for live demos and expert consultation. Get hands-on solutions to make your data management more efficient and reliable. See you there!


Shedding the Paper Weight, Rethinking Document Processing

The investment world is drowning in data. A lot of it is stuck in emails, portals, and PDFs. This makes tasks like risk management and reporting harder. We at Mesoica are building tools to help. Our system uses AI plus human-in-the-loop checks for fast and correct alternative investment data processing.


Mesoica to exhibit at Big Data Expo in Utrecht, NL

Excited to announce Mesoica's participation in this year's Big Data Expo, the ultimate event for data enthusiasts! Come and check out how our automated data quality processes and diverse workflow support can transform your business's data journey. Join us at our booth, and let's explore how to unlock the full potential of your data together. Stay tuned for more updates.


Mastering Data Quality

Explore effective strategies to maintain data quality as your organization grows. Learn about data governance, automation, investing in data quality tools, fostering a data-centric culture, and more in this insightful blog post.

Use Case

INREV SDDS Automation

Learn how Mesoica's data quality platform helped structure manual and error-prone data processes to an automated, controlled, and auditable data ingestion workflow. This post describes how we take INREV SDDS sheets and build a proper process around it.

How to

From Manual to Magical

Boost your data management process with our step-by-step guide to connecting your mailbox to Power Automate and the Mesoica Data Quality Platform. Learn how to automate data extraction and quality checks, streamlining your workflow and freeing up valuable time. Discover the power of automation and transform your data management strategy today.


From Quick Fixes to Long-Term Success

Many organizations grapple with scaling homegrown data quality solutions that have limitations in metric tracking, communication, and scalability. This article proposes transitioning from these short-term tactics to a strategic, long-term approach using platforms like Mesoica's for improved data quality management.


Small data, big problems

This post explains the impact of small data on data-intensive processes, and the challenges associated with common data containers used to exchange and process data such as Excel, PDFs, CSVs, and JSON/XML files. The author concludes that small data is a common problem in many organizations and a structured approach to dealing with it is not widespread.


Key process steps in data management

Data management follows four steps: Collection, from diverse sources; Validation, for quality assurance; Preparation, for user-specific needs; and Delivery, ensuring secure and efficient data transfer. Read on to learn more and unlock the power of effective data management!


Real world effective data management

Data mismanagement in financial institutions leads to operational inefficiencies and security issues. Traditional systems lack the required agility, causing reliance on insecure methods like email and Excel. A structured approach to data handling and continuous improvement is needed to bridge this gap.