Best Data Engineering Tools in Mexico

At K2View, we believe that every enterprise should be able to leverage its data to become as disruptive and agile as the best companies in its industry. We make this possible through our patented Data Product Platform, which creates and manages a complete and compliant dataset for every business entity – on demand, and in real time. The dataset is always in sync with its underlying sources, adapts to changes in the source structures, and is instantly accessible to any authorized data consumer. Data Product Platform fuels many operational use cases, including customer 360, data masking and tokenization, test data management, data migration, legacy application modernization, data pipelining and more – to deliver business outcomes in less than half the time, and at half the cost, of any other alternative. The platform inherently supports modern data architectures – data mesh, data fabric, and data hub – and deploys in cloud, on-premise, or hybrid environments.

Profile, cleanse, match and deduplicate data in drag-and-drop rules studio. Lo-code UI means no programming skill required, putting power in the hands of subject matter experts. Add AI & machine learning to your existing data management processes In order to reduce manual effort and increase accuracy, providing full transparency on machine-led decisions with human-in-the-loop. Offering award-winning data quality and matching capabilities across multiple industries, our self-service solutions are rapidly configured within weeks with specialist assistance available from Datactics data engineers. With Datactics you can easily measure data to regulatory & industry standards, fix breaches in bulk and push into reporting tools, with full visibility and audit trail for Chief Risk Officers. Augment data matching into Legal Entity Masters for Client Lifecycle Management.

Privacy engineering is an emerging field that has intersections with data engineering, information security, software development, and privacy law. Its goal is to ensure that personal data is stored and processed in a legally compliant way that respects and protects the privacy of the individuals this data belongs in the best possible way. Security engineering is on one hand a requirement for privacy engineering but also an independent discipline that aims to guarantee the secure processing and storage of sensitive data in general. If your organization processes data that is either sensitive or personal (or both), you need privacy & security engineering. This is especially true if you do your own data engineering or data science.