The Journey of Dview: Lessons Learnt from Solving Real-World Data Challenges

The Journey of Dview: Lessons Learnt from Solving Real-World Data Challenges

Building Dview has been nothing short of an adventure – a mix of late nights, breakthroughs and real-world lessons learned from tackling complex data problems.

One of the first issues we encountered was scalability. Most companies rely on initial solutions that make it easy to start their data-driven journey, but as the volume and velocity of data grows, these systems hit a wall. 

Beyond scalability, the journey from raw data to actionable insights is painfully slow. And for enterprises with hybrid structures – spanning multiple lake houses, warehouses and data sources, the process became even more cumbersome.

One moment that stands out is when we worked with a client whose data was spread across multiple platforms like Snowflake and Databricks. Getting a single, unified business view meant manually consolidating metrics, creating dashboards and then writing reports for their CXOs. It was tedious, error-prone and time-consuming!

That’s when we knew we needed a new approach and in the picture comes our three core capabilities:

  1. Fiber - which centralizes data effortlessly, connecting 100+ sources to provide a unified view in near-real time 
  2. Aqua - which queries data seamlessly delivering instant insights at scale with no query latency
  3. Dsense - which is all about hyperscale AI driven unified analytics – actionable insights in under 50 seconds, without moving data – transforming raw data into forecasts

These solutions were born out of necessity, from listening to clients and adapting to their pain points. 

The result of them coming together? 

Faster analytics, lower costs and an end to data silos. Together, they transform the data journey!

They bring data together from diverse sources, create visualizations automatically and generate insights that go far beyond charts. Seasonal trends, business impacts, forecasts – everything is analyzed and explained in-depth. This means organizations can go from raw data to decisions in record time.

We’ve seen businesses go from struggling to make sense of their data to unlocking growth opportunities with ease.

We’ve worked across industries like Fintech, Healthtech and Industrial sectors, and you know what the biggest lesson from this journey is? Real-world data problems demand real-world solutions.

For us, this journey is about more than building tools. It’s about helping businesses turn complexity into clarity! 





Pratyaksh Agarwal, CFA

Co-Founder MlympiX | London Business School | BITS Pilani

1w

Superb!

Hanabal Khaing

Senior Enterprise Data Modeler Data consultant CDO CTO Law & BRD to Multidimensional legal compliance real-time anti-fraud Data Model, UML 60 SKILL SETS, 5-day data structure security analysis pre and post breach $50,000

1w
Vineet Agarwal

Business Builder | Climate Tech | Data & Analytics | Research & Insights

1w

Kauts Shukla you guys are solving extremely important problems in the data space. Keep at it!

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