Business Objectives, Data Analytics, Data Transformation and Data Warehouse

Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue

AWS Big Data

JULY 31, 2023

This solution decouples the ETL and analytics workloads from our transactional data source Amazon Aurora, and uses Amazon Redshift as the data warehouse solution to build a data mart. We use Amazon Redshift as the data warehouse to implement the data mart solution. Sumitha AP is a Sr.

Sales

Sales Data Warehouse Visualization Testing

Building Better Data Models to Unlock Next-Level Intelligence

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. This design philosophy was adapted from our friends at Fishtown Analytics.).

Modeling

Modeling Big Data IoT Data Warehouse

Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. However, data mesh is not about introducing new technologies.

Data-driven

Data-driven Data Lake Data Quality Business Objectives

Data Leaders Brief

Migrate your existing SQL-based ETL workload to an AWS serverless ETL infrastructure using AWS Glue

Building Better Data Models to Unlock Next-Level Intelligence

Data Mesh 101: How Data Mesh Helps Organizations Be Data-Driven and Achieve Velocity

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