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Lakehouse Days: September Edition || Practice PySpark, SQL, and DSA problems with us
About the event
Join us for an exclusive in-person event on "Practicing PySpark, SQL, and DSA problems for Data Engineering interviews," hosted by e6data. This meetup is specifically designed for aspiring data engineers, data analysts, and data scientists who are currently preparing for interviews, and looking for peer support and guidance. We will meet informally to discuss and solve various questions together.
Meet the mentors
Padmapriya Uppala, Senior Data Engineer, Visa
Topic: Practice questions from the Hyperlocal domain
Padma will assist you in solving multiple PySpark, Pandas, and MySQL questions related to Hyperlocal delivery. She will help you enhance the skills typically required for the first round of interviews at a product-based company.
Time: 9:00 - 10:30 AM IST
Sai Vineel, Senior Data Engineer at Walmart
Topic: Practice question from the Retail domain
Sai will assist you in solving multiple PySpark, Pandas, and MySQL questions related to the E-commerce domain. He will help you enhance the skills typically required for the first round of interviews at a product-based company.
Time: 10:45 - 12:00 PM IST
Ankur Ranjan, Senior Software Engineer, e6data
Topic: Panel discussion on emerging use cases and developments in the lakehouse ecosystem
Ankur will help you solve multiple DSA questions commonly asked in interviews. He will assist you in improving the skills required for the first round of interviews at a product-based company.
Time: 12:30 - 01:15 PM IST
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Pick a heavy workload
Choose a common cross-industry "heavy" workload; OR Work with our solution architect team to identify your own.
Define your 360° interop
Define all points of interop with your stack: e.g. Catalog, BI Tool, etc. e6data is serverless first and available on AWS/Azure.
Pick a success metric
Supported dimensions: Speed/Latency, TCO, Latency Under Load. Pick any linear combination of these three dimensions.
Pick a kick off date
Assemble your team (data engineer, architect, devOps) for kickoff from the date of kickoff, and go live in 10 business days.
Frequently asked questions (FAQs)
We are universally interoperable and open-source friendly. We can integrate across any object store, table format, data catalog, governance tools, BI tools, and other data applications.
We use a usage-based pricing model based on vCPU consumption. Your billing is determined by the number of vCPUs used, ensuring you only pay for the compute power you actually consume.
We support all types of file formats, like Parquet, ORC, JSON, CSV, AVRO, and others.
e6data promises a 5 to 10 times faster querying speed across any concurrency at over 50% lower total cost of ownership across the workloads as compared to any compute engine in the market.
We support serverless and in-VPC deployment models.
We can integrate with your existing governance tool, and also have an in-house offering for data governance, access control, and security.
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