̲𝐏̲𝐫̲𝐨̲𝐛̲𝐥̲𝐞̲𝐦̲
Analysts and business teams in T.EN often spent hours together per query of data reconsiling insights from multiple scattered sources - ̲𝒔̲𝒏̲𝒐̲𝒘̲𝒇̲𝒍̲𝒂̲𝒌̲𝒆(internal data warehouse), ̲𝑹̲𝒚̲𝒔̲𝒕̲𝒂̲𝒅̲,̲ ̲𝑩̲𝒍̲𝒐̲𝒐̲𝒎̲𝒃̲𝒆̲𝒓̲𝒈̲,̲ ̲𝑺̲𝒂̲𝒍̲𝒆̲𝒔̲𝒇̲𝒐̲𝒓̲𝒄̲𝒆̲ and other market intellignece providers. This slowed down decision-making in large-scale EPC projects (𝐡𝐲𝐝𝐫𝐨𝐠𝐞𝐧, 𝐞𝐭𝐡𝐲𝐥𝐞𝐧𝐞, 𝐂𝐂𝐔𝐒). .
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̲𝐀̲𝐩̲𝐩̲𝐫̲𝐨̲𝐚̲𝐜̲𝐡
- 𝗗𝗮𝘁𝗮 𝗜𝗻𝗴𝗲𝘀𝘁𝗶𝗼𝗻 & 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Designed and developed pipelines to collect structured & semi-structured data from snowflake, Rystad, Bloomberg, and other subscription feeds.
- 𝗖𝗹𝗼𝘂𝗱 𝗘𝗻𝘃𝗶𝗿𝗼𝗻𝗺𝗲𝗻𝘁: Built entirely in the Azure ecosystem (Azure Data Factory, Azure Functions, Synapse Analytics, Logic Apps).
- 𝗣𝗿𝗼𝗰𝗲𝘀𝘀𝗶𝗻𝗴 & 𝗦𝘁𝗼𝗿𝗮𝗴𝗲 : Unified datasets within Snowflake for scalable querying and analytics.
- 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻 : Connected curated data streams to Salesforce and other internal tools, enabling commercial and strategy teams to directly access insights.
- 𝗔𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻: Implemented scheduling, logging, and monitoring for pipeline reliability.
--- ̲𝐀̲𝐫̲𝐜̲𝐡̲𝐢̲𝐭̲𝐞̲𝐜̲𝐭̲𝐮̲𝐫̲𝐞̲
[Data Sources : Snowflake/Rystad /Bloomberg] -> [Azure Data Factory + Functions] -> [Snowflake(Unified)] ->[Salesforce PowerBI]
̲𝐓̲𝐞̲𝐜̲𝐡̲ ̲𝐒̲𝐭̲𝐚̲𝐜̲𝐤̲ ̲
- 𝗖𝗹𝗼𝘂𝗱 : Azure Data Factory, Azure Functions, Azure Synapse
- 𝗗𝗮𝘁𝗮 : Snowflake, Rystad, Bloomberg, other EPC data providers
- 𝗜𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗶𝗼𝗻: Salesforce, Power BI for dashboards
- 𝗣𝗿𝗼𝗴𝗿𝗮𝗺𝗺𝗶𝗻𝗴 : Python (ETL/ELT scripts), SQL
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̲𝐎̲𝐮̲𝐭̲𝐜̲𝐨̲𝐦̲𝐞̲ ̲
- Reduced query resolution time from 45 minutes to under 2 minutes.
- Improved data accessibility for cross-functional teams (engineering, procurement, sustainability, and commercial).
- Achieved 70%+ adoption within 2 months, accelerating EPC decision-making and strengthening data-driven project evaluations.