Lyftrondata
Asad Ali has a strong background in software development, with experience in various roles. Asad is currently working as a Full-stack Developer at Lyftrondata since January 2022. Prior to this, they worked as a Back End Developer and DevOps Engineer at HyperNym starting from April 2020. Before that, they served as a Python Django Developer at VECDEN Technologies from April 2019 to February 2020. Asad also worked as a Python Developer at Alberuni Tech from October 2018 to April 2019. Their career started as an Intern at AKSA-SDS from July 2017 to September 2017.
Asad Ali obtained a Bachelor's degree in Computer Software Engineering from the National University of Modern Languages. Asad attended the university from 2014 to 2018.
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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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