EVL Tool

Breaking NEWS

➡️ We are working on making QVD available also on Windows!

EVL QVD Utils enables reading and writing to QVD files without using Qlik Sense or QlikView.

Check our website: https://www.evltool.com/en/evl-qvd-utils

EVL Manager provides a diagram of the DAG, so developers and Operations personnel can easily review the flow of data.

Monitor Operations
Check job status from mulitple deployments simultaneously. View current status, start, stop, rerun jobs

https://www.evltool.com/en/evl-manager

◾️ EVL Manager ◾️

Manage Multiple Deployments in a Single View and run EVL microservices, jobs, and workflows.
Graph data workflows with EVL Manager's visual inspection tools. Monitor operations and resource consumption.

Available for Windows, Mac, and Linux.

➡️ https://www.evltool.com/en/evl-manager

➡️ EVL Data Generation

If you're developing an application, you'll want to make sure you're testing it under conditions that closely simulate a production environment.

When your test database is filled with realistic looking data, you'll be more engaged as a tester. When you demonstrate new features to others, they'll understand them faster.

Try EVL Data Generation for cost-effective data generation.

More information:
https://www.evltool.com/en/evl-data-generation

We would like to express our sincerest appreciation for the trust you have placed in us and best wishes for the holidays. 🎄

Team EVL Tool

EVL Tool - QVD Utils News

Following new options to qvd2csv were introduced:

--filter=
read only records with given .

--first-record=
start to read from the record number .

--guess-uniform-symbol-size
might speed up indexing of dictionary, but it could not work in all cases. Use only in special cases when need really good performance.

--low-memory
do not read dictionary into memory. This could save memory consumption, but slows down reading the source file.

These new options help to read huge QVD files as fast as possible.

So now it is possible either to cut only particular fields from QVD (option --match-fields)or to cut only particular rows (options --first-record or --filter).

More information: https://www.evltool.com/en/evl-qvd-utils

What is anonymization of data?

Data anonymization is the processing of data with the aim of irreversibly preventing the identification of the individual, so that the person can no longer be identified directly or indirectly.

It will be impossible to connect data to an individual for it to meet the requirements for data anonymization. Anonymization and GDPR compliance – there is no standard technique in EU legislation.

For more information visit our website:
https://www.evltool.com/en/evl-data-anonymization

👉 EVL Microservices are built on top of the core EVL software and retain its flexibility, robustness, high productivity, and ability to read data from various sources;
including JSON and Excel files, databases—Oracle, Teradata, PostgeSQL, etc.—and streaming data like Kafka.

🤓 Would you like to try our Microservices? No problem, check our website and try our free trials.

https://www.evltool.com/en/downloads

Convert .qvd ↔ .csv

▪️ Using QVDs you can share data between multiple applications without having to keep going back to the source data, you can also chunk up the data load process into manageable steps.

◾️ Why you should use qvd:
- Ability to do parallel data extracts
- Easier unit testing of parts of the load process
- Incremental loads
- Sharing of extracted data between presentation apps
- Ability to scale the solution when data volumes grow
- Ability to delegate responsibility for different parts of the data load to different teams

TRY FOR FREE
https://www.qvdconvert.com

Advantages of Data Anonymization

- Data anonymization is a method of ensuring that the company understands and enforces its duty to secure sensitive, personal, and confidential data

- Data anonymization increases the governance and consistency of results. Clean, accurate data allows you to leverage apps and services and preserve big data analytics and privacy.

EVL Data Anonymization
one of the techniques that organizations can use to adhere to strict data privacy regulations that require the security of personally identifiable information (PII), such as health reports, contact information, and financial details.

https://www.evltool.com/en/evl-data-anonymization

◾️ EVL Data Anonymization ◾️

Compliance with GDPR can be challenging for many organisations and the potential fines can be daunting.

Anonymization eliminates personal data so that data subjects can no longer be identified. Anonymized data is excluded from GDPR regulation altogether because anonymized data is no longer personal data.

EVL Data Anonymization Microservice can be used for pseudonymization and anonymization of production data according to GDPR requirements, as well as for the protection of commercially sensitive data from developers, testers, and other outside contractors.

https://www.evltool.com/en/evl-data-anonymization