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I will do big data analytics using pyspark, sql and python
I will design and develop your website, mobile app with AI automation
I'm a UI/UX designer and web developer who turns ideas into high-performing digital products. From mobile app design and WordPress development to landing pages and dashboards, I craft pixel-perfect in...
Level 1
Has met certain performance criteria and shows strong potential in the marketplace.
About this Gig
Is your data too large for Excel or pandas? I process and analyze big data with PySpark, Spark SQL and Python so you get fast, scalable answers.
I am K. M. Arafat Islam, Founder and CEO of BuildSign Digital, CSE graduate with 4 years of experience and 15 published papers in Springer and IEEE venues, including big data analytics research.
What I do: PySpark DataFrame and Spark SQL analysis Data cleaning, joins, aggregations and window functions ETL pipelines from CSV, Parquet, JSON or SQL databases Query and job optimization (partitioning, caching) Databricks, Google Colab or local Spark setup Spark MLlib models on large datasets Visual summaries and dashboards of results
You receive: Commented PySpark notebook or scripts Output tables in CSV, Parquet or SQL Charts and a short findings report
Message me your data size, format and goal before ordering so I can recommend the right package.
My Portfolio
FAQ
How big can my data be?
From a few GB to hundreds of GB, depending on your environment. For very large data, I work inside your Databricks or cloud workspace.
Do I need Databricks?
No. I can use Google Colab or a local Spark setup for moderate sizes, or your Databricks, AWS EMR or Azure environment.
Can you optimize my slow Spark job?
Yes. Send the code and I will profile it and apply partitioning, caching, broadcast joins and better transformations.
Do you also write SQL only?
Yes. Complex SQL queries, CTEs and window functions for MySQL, PostgreSQL, SQL Server or Spark SQL are all included.
Is my data secure?
Yes. I can work on sample data, anonymized data or inside your own workspace with limited access.
