Hassan Uppal

Senior Software Engineer at Lyftrondata

Hassan Uppal has a strong background in software engineering and web development. Hassan is currently working as a Senior Software Engineer at Lyftrondata since September 2021. Prior to this, they worked at Ashtex Solutions as a Web Developer from September 2015 to December 2021. Additionally, they gained experience as a Software Engineer at MonetizeMore from February 2018 to September 2021.

Hassan Uppal completed their Fsc in Pre Engineering from Punjab College Gujranwala, from 2008 to 2010. Hassan then pursued their Bachelor of Business and Information Technology, specializing in Information Technology, from the University of the Punjab, from 2011 to 2015.

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Lahore, Pakistan

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Lyftrondata

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Lyftrondata eliminates the time spent by engineers building data pipelines manually and makes data instantly available for insights on data hub. Lyftrondata Key Differentiators: > Create a Data Pipeline in Minutes: Register over 100+ types of data sources in one place. Choose the most valuable data sources and replicate them to the cloud. > Power Modern Delta Lake & Data Warehouse: Lyftrondata enables you to build a modern data warehouse and data lake in just a few clicks. Normalize all data sets and load the data to the data warehouse. Apply complex transformations with SQL when needed. > Shortens Time-to-insights: Empower data-savvy users to find and prepare the data they need for analytics. Enable real-time access to any data source from any BI tool. > Unlimited Compute: Lyftrondata enables you to compute on Databricks Spark and Snowflake. Thus, you have the flexibility to choose to compute on either of these modern platforms. > Integrate Multiple Clouds: Build a single view of data across different clouds and regions. Replicate data between different regions of the clouds and put them in sync. > Phase Transition to the Cloud: Migrate on-premise data warehouses to the cloud step-by-step. Create data pipelines for migrated data warehouses and legacy data warehouses in real-time. Not all data warehouses may be moved to the cloud in one step. > Build an Agile Data Culture: Empower data users to find and prepare the data they need in analytics. A fast data strategy based on a combination of a modern data pipeline and real-time data saves delays in data preparation. > Ensure Data Governance in the Cloud: Build a searchable data catalog of valuable data sources. Apply table, row, and column security to any data source on-premise, SaaS, or in the cloud. Build a governed data lake integrated with the enterprise active directory for authentication.


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51-200

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