Mageâ„¢ is the leading solutions provider for data security and data privacy software for global enterprises. Built upon a patented and award-winning solution, the Mage platform enables organizations to stay on top of privacy regulations while ensuring security and privacy of data. Top Swiss Banks, Fortune 10 organizations, Ivy League Universities, and Industry Leaders in the financial and healthcare businesses protect their sensitive data with the Mageâ„¢ platform for Data Privacy and Security. Deploying state-of-the-art privacy enhancing technologies for securing data, Mageâ„¢ delivers robust data security while ensuring privacy of individuals.
Visit www.magedata.ai to explore the brand’s new website and to check out the company’s solutions.
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Mage Data's answer
Mage is targeted towards enterprises that have a diverse data landscape – from mainframes to relational databases, to more modern cloud-based databases, file servers (on-premise or on-cloud) as well as SaaS application. From a single, enterprise-wide platform, Mage enables stakeholder collaboration to drive data security policy through the use of patented solutions, including data discovery and classification, the use of privacy enhancing/preserving techniques, static & dynamic data masking, database activity monitoring, DSAR automation, etc. Using a zero-trust, no-code approach, Mage enables enterprise-wide security, regulatory compliance by taking a risk-elimination approach. We have enabled global leaders share data confidently while reducing the risk of carrying sensitive data by up to 95%.
The Mage platform holistically provides coverage for data security right from data discovery, data anonymization, activity monitoring, and Data Subject Access Rights Automation all in a single solution.
Mage Data's answer
• One-stop shop for data security
• Built from the ground up – so shared intelligence, easy deployment, etc Most, if not all competition products are built through acquisitions or partnerships, and are rarely built from the ground up. The Mage platform is a single, integrated platform that has been purpose-built to solve the issue of data security faced by global enterprises. Being a single integrated platform, each of the product modules work seamlessly across the platform and the intelligence can be shared across the modules. While Mage provides capabilities within the individual modules, it can also integrate seamlessly with existing solutions that organizations may possess to ensure smooth functioning with the IT landscape of the customer.
• Unlike most of our competitors, the Mage platform is compatible with a wide variety of data stores that include both, the legacy data stores, as well as the new gen data stores, hosted on either cloud or on-premise.
Mage Data's answer
You can read our story at https://magedata.ai/company/about/brand-story/
Based on our record, Jupyter seems to be more popular. It has been mentiond 206 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Interesting, I would have guessed you had used something jupyter-like: https://jupyter.org/ https://explorabl.es/all/. - Source: Hacker News / 29 days ago
JupyterLab: JupyterLab is an interactive development environment that allows you to create and share documents containing live code, equations, visualizations, and narrative text. It's particularly well-suited for data science and research-oriented projects. - Source: dev.to / about 2 months ago
Jupyter Lab web-based interactive development environment. - Source: dev.to / 2 months ago
Choosing IDE: Selecting a suitable Integrated Development Environment (IDE) is crucial for efficient coding. Consider popular options such as PyCharm, Visual Studio Code, or Jupyter Notebook. Install your preferred IDE and ensure it's configured to work with Python. - Source: dev.to / about 2 months ago
Jupyter Notebooks is very popular among data people specially Python users. So, I tried to find a way to run the Groovy kernel inside a Jupyter Notebook, and to my surprise, I found a way, BeakerX! - Source: dev.to / 3 months ago
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