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Data Engineering

Optimizing Data Pipelines and Engineering Solutions in GCP using Apache Spark and pyspark

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Optimizing Data Pipelines and Engineering Solutions in GCP using Apache Spark and pyspark

Optimizing Data Pipelines and Engineering Solutions in GCP using Apache Spark and pyspark

Background A leading provider of advanced data solutions, was experiencing significant performance bottlenecks in its data processing pipelines. The company relied on legacy systems that could not keep pace with rapidly growing data volumes, leading to delays in analytics and reporting. These issues not only hampered operational efficiency but also increased operational costs and customer …

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Implementing Informatica MDM for a Banking Institution (On-Prem)

Introduction In the modern banking industry, maintaining a single, trusted view of customer data is critical for regulatory compliance, risk management, and personalized customer experiences. This case study outlines the implementation of an Informatica Master Data Management (MDM) on-premises solution for a large banking institution with multiple legacy systems.   Problem Statement The problem statement …

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