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Are you drowned in data? Use AI to Make sense of it

A brilliant idea is where it all starts from. Consider a dedicated news advisor delivering relevant information based on your personal reading habits, without you having to sort it. This does sound fascinating and luckily it’s already here, in the Hotify Avatar. What Hotify is – It’s an Intelligent Information Discovery Engine designed to cater the needs of each individual content consumer.

Hotify’s goals are clear, delivering high quality information to its users based on their personal reading habits and requirements. It serves the purpose well, by being one step ahead of the competition using the principles or AI and Machine Learning. What does this help with?  You may ask, it addresses the problems faced by users due to the large amount of information floating on the Internet.  The platform learns, calibrates and then delivers you the content you need, all possible via Machine learning & A.I based development.

Data Science

“Machine Learning is the core of Hotify. All our theories, algorithms translate into Machine Learning based algorithms to deliver personalized content to our users. Right from a simple probability model of what users would love to read in general, to a complicated graph based deduction of what the users would like to read next or now, is all driven using Machine learning as a tool. It is very similar to a giving a dedicated news assistant for every user as we evolve the product”   

– Ankur Dinesh Garg(Founder, Hotify)

The process of gathering efficiently sorted information where the user doesn’t have to make the effort of choosing which publication or topic to follow, and by eliminating manual curation it cuts down the delay between relevant news getting out and reaching the user, this is done by Data Science.

Hotify is partnering with MantraLabs to solve the data science problem and make sense of the huge stacks of data. This is being done by processing the collected data through AI Engine to learn the preferences for user and providing relevant content. The more you use the system the smarter it becomes in providing relevant news items.

Read more about MantraLabs at https://www.mantralabsglobal.com

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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,