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MLens

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Software Status:Active

About MLens

MLens is a data management software from Knowledge Lens that provides insights into data utilization and governance. It combines data cataloging, data lineage tracking, and automated metadata management so organizations can maintain compliance and monitor data quality. MLens enables users to gain visibility into their data ecosystem, facilitating better decision-making. The platform supports various data sources and integrates with existing analytics tools to provide a comprehensive view of data flows and dependencies. Key capabilities: data cataloging data lineage tracking metadata management compliance monitoring integration with analytics tools Best for: data governance teams that need to manage and improve data usage.

MLens Details

Vendor
Knowledge Lens
Year Launched
2013
Location
74/A, Electronic City Phase 1, Bengaluru, Karnataka 560100
Deployment
cloud
Training Options
live online, in person
Countries Served
All Countries
Languages
English, Spanish, French, German, Italian, Japanese, Chinese
Users
Manufacturing Pharma Finance Oil and Gas Retail
Industries Served
Healthcare, Education, Finance, Retail, Technology, Manufacturing, Government, Marketing.
Tags
Big Data Experts, Internet of Things, Data Science, Big Data Infrastructure Capacity Planning and Administration, Analytics, Reporting, AI, MachineLearning, Blockchain, Cloud Computing, AWS, Azure, Google Cloud Platform, DevOps, Environmental Monitoring, Healthcare, Manufacturing, Big Data Security, Enterprise Data Lake, Big Data Backup & DR, and Next Generation Enterprise Data Lake

MLens's In-App Market Place

Does MLens have an in-app market place?

Yes

How many Mini-Apps in the marketplace?

0

Mini Apps

Pricing Options

Free trial
Free version
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Promo Offer

Accepted Payment Currencies

USD ($), EUR (€), GBP (£), JPY (¥), AUD (A$), CAD (C$), CHF (Fr), CNY (¥), SEK (kr), NZD (NZ$), INR (₹), RUB (₽), ZAR (R), KRW (₩), HKD (HK$)

Pros & Cons

  • 1. Powerful Analytics: Leveraging machine learning for advanced data analysis and predictive modeling.
  • 2. Scalability: Can handle large datasets and scale as data volumes increase.
  • 3. Comprehensive Data Processing: End-to-end data preparation and analysis workflow.
  • 4. Real-Time Insights: Provides actionable insights in real time, helping businesses make data-driven decisions.
  • 5. Customization: Allows businesses to tailor models and analytics to their specific needs.
  • 1. Learning Curve: There may be a steep learning curve for non-technical users, especially in terms of model building.
  • 2. Requires Expertise: For advanced features, users may need a background in data science or machine learning.
  • 3. Limited Out-of-the-Box Features: Some users may need additional customization to fully integrate with their existing systems.
  • 4. Data Privacy Concerns: Handling sensitive business data may require compliance with industry standards or regulations.

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