Cloud Design Goals
Improving data queries, pipelines
On real world projects and deployments, you hear the lament that a datawarehouse or data engine ‘does not work’. Query response times are slow, it …
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AWS TechnologyRelational, Document, Key Value Databases: summary, use cases
There are a wide variety of databases. With cloud and hybrid architectures often see the following: Relational DB A structured format with rows and columns, re…
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AWS TechnologyBatching and AWS S3 on prem to S3 cloud
A useful architecture to move data from on-premises to AWS is to consider using AWS S3 outputs and move data directly over a Direct Connect to S3 in AWS. This …
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DataAWS DataBase Migration Service Overview
AWS Database Migration Service or DMS is a mature process to move on premises data to the AWS cloud, including to a S3 Data Lake. It is not recommended that fi…
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DataData Platform Automation
The problems with Data Pipelines and the hydration of a Data Lake include: Data teams often end with technical debt surrounding CI/CD, IaS, observability, and …
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AgileDataLake and its Challenges
DataLake The entire concept of a Data Operations Platform rests on top of a Data Lake. There is no simple definition of a Data Lake, but based on the author’s …
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AgileData Operations + Agile
Data Operations ‘DataOps’ has been inspired by the Agile-premised ‘Development Operations’ model. The ‘DevOps’ model which usually includes security (DevSecOps…
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Cloud ModelsApache Iceberg: an overview
The icebergth is hereth. Apache Iceberg is an open-source table format for large-scale data systems, designed to provide efficient and reliable management of s…
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DataDatabricks Lakeflow (replaces Airflow)
Databricks LakeFlow is built on top of Databricks Workflows and Delta Live Tables. It is an implementation of Apache Airflow built into the Databricks eco syst…
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