Common Mistakes in DBT That Can Lead to Performance and Operational Issues

DBT (Data Build Tool) is a powerful framework for data transformation, but like any powerful tool, small missteps can lead to big issues — especially at scale. In this post, I’ll walk you through three common pitfalls I’ve seen in production DBT projects that can cause performance degradation, operational issues, or incorrect lineage tracking — […]

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Hands-on practice for joining multiple SCD2 tables to make consolidated SCD2 in Data Warehousing

Concept of SCD-2 Slowly Changing Dimension (SCD) SCD Type 1: Overwrites the existing value with the new value and does not retain history. SCD Type 2: Adds a new row for the new value and maintains the existing row for historical(inactive) and reporting purposes. SCD Type 3: Creates a new current value column in the

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How Hadoop and Spark Are Transforming Data Warehousing

Traditional data warehouses cannot handle big data. Hadoop, Spark, Impala, Parquet and SQL on Hadoop will play big role in data warehouse modernization. The nature of data that enterprises have been dealing with has been changing in the last few years. It is no longer just transactional data. Volume, velocity, and variety of data is

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Releasing Soon! Learning Elastic Stack 6.0

The book Learning Elastic Stack 6.0 is available for pre-order. Here is what to expect from the book. Elasticsearch has been at the forefront of the big data movement. Since its initial release in 2010, it has slowly but steadily evolved into a robust big data store. The rich ecosystem of components around Elasticsearch – Logstash, Kibana,

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