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India’s technology revolution since 1947

We are wishing you a very Happy Independence Day. We are celebrating our 72nd independence day this August 15th and it occurred to us that we have come a long way from being a under developed country ruled by the British to one of the most promising economies of the developing world. We have a great market and huge talent pool to fuel our growth. Though still a developing country, has achieved a lot in the past 71 years. One of the fields in which India has made huge achievements is Science and Technology and has seen the technology revolution.

Let’s have a little recap:

 

Thinking back we have come a long way from being a agrarian country to a premier, technology fuelled, IT exporter. We have grown in all areas technology. Over the years we have touched almost all dimensions of technology evolution. From Industrial growth to automated factories. From manual labor based farming to AI powered farming assistants. From bullock carts to creating AI powered self driving cars. From local shops to globally sourced online market places. From barter trade to Electronic funds transfer over mobiles.

We are proud to be a part of this technology revolution and are focusing on the trends in the IT industry in the last 10 years and relate them to how this has shaped Mantra Labs. We have also updated ourselves as the technology around us took shape. We were the pioneers of the Indian Online market place, now we are shaping the future of Industries with Artificial intelligence based applications. We are primarily focused on intelligent automation of processes and experts in the Insurance industry. We are keeping up with all the developments in technology and not only do we follow the development we help shape them as well. 

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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