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Pawan Tat

Data Engineer

Pawan Tat is a Data Engineer at Algoscale with hands-on experience in Big Data technologies and cloud-based data solutions. He has spent over three years building scalable data pipelines and processing large volumes of data across Azure, AWS, and Microsoft Fabric. His core toolkit includes Spark, Scala, PySpark, Python, and SQL. Pawan approaches data engineering with a clear focus on efficiency and impact: every pipeline he builds is designed not just to move data, but to enable smarter, faster decision-making across the organizations he works with.

Blog posts by this author

Running a Data Lake in the Cloud

Running a Data Lake in the Cloud: What Actually Changes Day to Day

A lot gets written about the conceptual shift from on-premise to cloud infrastructure – elasticity, cost models, the security paradigm change. Less

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Data Lake vs Data Lakehouse

Data Lake vs Data Lakehouse: What’s Actually Different

“Data lake” and “data lakehouse” get used almost interchangeably in a lot of casual conversations – and vendor marketing doesn’t always help

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Key Components of Data Lakehouse

Data Lakehouse Meaning and Key Components, Explained Simply

Data lakehouse (noun) – a data storage and analytics system that combines the low cost and flexibility of a data lake with

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What Is a Data Lakehouse

What Is a Data Lakehouse

If you have been reading about data infrastructure lately, you have probably heard the word “lakehouse” a lot, alongside terms like ACID

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open source lakehouse

Is an Open Source Lakehouse Right for Your Data Stack

A fully open source lakehouse – built from components like Apache Iceberg, Trino, and an open catalog like Nessie or Apache Polaris,

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Azure Data Lake vs Azure Data Lakehouse

Azure Data Lake vs Azure Data Lakehouse: Picking the Right Model

Within Azure specifically, the same question keeps coming up: is Azure Data Lake Storage Gen2 on its own enough, or do you

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AWS Data Lake vs AWS Lakehouse

AWS Data Lake vs AWS Lakehouse: Which One Fits Your Data

Inside AWS specifically, this question comes up constantly: do you need a plain data lake – S3, Glue, Athena – or a

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IN-HOUSE TEAM VS. MICROSOFT FABRIC CONSULTING SERVICES

IN-HOUSE TEAM VS. MICROSOFT FABRIC CONSULTING SERVICES

Every organization sitting on a growing pile of data eventually faces the same fork in the road: build the capability internally, or

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Cloud-Native BI Architecturewith Power BI

Why Business Intelligence Consulting Companies Are Key to Cloud-Native Digital Transformation

Cloud-native digital transformation is the shift from on-premises infrastructure and legacy systems to architectures that are built for the cloud from the

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BI Partner Evalution Framework

Top 10 Mistakes Businesses Make When Choosing a BI Consulting Firm

Choosing the wrong bi consulting firm costs more than the engagement fee. A poorly designed Power BI environment requires remediation that often

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