Try : Insurtech, Application Development

AgriTech(1)

Augmented Reality(20)

Clean Tech(8)

Customer Journey(17)

Design(45)

Solar Industry(8)

User Experience(68)

Edtech(10)

Events(34)

HR Tech(3)

Interviews(10)

Life@mantra(11)

Logistics(5)

Strategy(18)

Testing(9)

Android(48)

Backend(32)

Dev Ops(11)

Enterprise Solution(29)

Technology Modernization(8)

Frontend(29)

iOS(43)

Javascript(15)

AI in Insurance(38)

Insurtech(66)

Product Innovation(58)

Solutions(22)

E-health(12)

HealthTech(24)

mHealth(5)

Telehealth Care(4)

Telemedicine(5)

Artificial Intelligence(147)

Bitcoin(8)

Blockchain(19)

Cognitive Computing(7)

Computer Vision(8)

Data Science(23)

FinTech(51)

Banking(7)

Intelligent Automation(27)

Machine Learning(47)

Natural Language Processing(14)

expand Menu Filters

2016 – A big leap for Mantra Labs

BLOG2-1

When this year started Mantra Labs was adjusting to the new world view of technology. We were embracing IOT, AI and cloud along with our core strengths in Mobile and Web technologies.

It is a pleasure to look back and reflect on what we have achieved in this year.

  • Started Mantra.AI to solve business problems through the use of Artificial Intelligence techniques.
  • Initiated Mantra IOT labs to start creating working prototypes for some cool ideas on home automation
  • Started an office in USA to drive our business in the North American market.
  • We added multiple client to our portfolio in AI, enterprise and consumer internet including industry leading health insurance provider.
  • We are now accredited partners for
  • Strategic partnerships with
    • Toshiba for IOT in USA
    • WD Creative for Analytics in  USA
    • CP Moksha for Financial Technology in UK
    • Finocracy for Financial Technology in Middle East
  • We prominently focused in following media events
    • JS framework Meetups
    • Hackathon based on IBM Watson
    • Partnered for Startup Master Class.

While the year was great we aim to achieve even more in 2017.

The areas to look for would be:

  • The products incubated by us.
    • SellfashAutomating Supplier-Reseller Chain. 350+ Suppliers already onboard.
    • TouchkinAl healthcare startup – raised seed funding
  • IOT products for home automation

For more information https://www.mantralabsglobal.com

Follow us on linkedIn and Facebook to know more.

Cancel

Knowledge thats worth delivered in your inbox

Silent Drains: How Poor Data Observability Costs Enterprises Millions

Let’s rewind the clock for a moment. Thousands of years ago, humans had a simple way of keeping tabs on things—literally. They carved marks into clay tablets to track grain harvests or seal trade agreements. These ancient scribes kickstarted what would later become one of humanity’s greatest pursuits: organizing and understanding data. The journey of data began to take shape.

Now, here’s the kicker—we’ve gone from storing the data on clay to storing the data on the cloud, but one age-old problem still nags at us: How healthy is that data? Can we trust it?

Think about it. Records from centuries ago survived and still make sense today because someone cared enough to store them and keep them in good shape. That’s essentially what data observability does for our modern world. It’s like having a health monitor for your data systems, ensuring they’re reliable, accurate, and ready for action. And here are the times when data observability actually had more than a few wins in the real world and this is how it works

How Data Observability Works

Data observability involves monitoring, analyzing, and ensuring the health of your data systems in real-time. Here’s how it functions:

  1. Data Monitoring: Continuously tracks metrics like data volume, freshness, and schema consistency to spot anomalies early.
  2. Automated data Alerts: Notify teams of irregularities, such as unexpected data spikes or pipeline failures, before they escalate.
  3. Root Cause Analysis: Pinpoints the source of issues using lineage tracking, making problem-solving faster and more efficient.
  4. Proactive Maintenance: Predicts potential failures by analyzing historical trends, helping enterprises stay ahead of disruptions.
  5. Collaboration Tools: Bridges gaps between data engineering, analytics, and operations teams with a shared understanding of system health.

Real-World Wins with Data Observability

1. Preventing Retail Chaos

A global retailer was struggling with the complexities of scaling data operations across diverse regions, Faced with a vast and complex system, manual oversight became unsustainable. Rakuten provided data observability solutions by leveraging real-time monitoring and integrating ITSM solutions with a unified data health dashboard, the retailer was able to prevent costly downtime and ensure seamless data operations. The result? Enhanced data lineage tracking and reduced operational overhead.

2. Fixing Silent Pipeline Failures

Monte Carlo’s data observability solutions have saved organizations from silent data pipeline failures. For example, a Salesforce password expiry caused updates to stop in the salesforce_accounts_created table. Monte Carlo flagged the issue, allowing the team to resolve it before