Accelerate Your Journey to a Modern Data Platform Using Coalesce

Accelerate Your Journey to a Modern Data Platform Using Coalesce<b>Abstract </b>Most organizations face challenges while adapting to data platform modernization. The critical challenge that data platforms have faced is improving the scalability and performance of data processing due to the increased volume, variety, and velocity of data used for analytics.This article aims to summarize answers to the challenging questions of data platform modernization, and here are a few questions:How can we onboard new data sources with no code or less code?What steps are required to improve data integrity among various data source systems?How can CI/CD (continuous integration/continuous development) workflows across environments be simplified?How can we improve the testing process?How do we identify data quality issues early in the pipeline?As data platforms become more complex, managing them becomes difficult, and embracing the Data Operations principle is the way to address data operation challenges. We will look into the capabilities of ETL Frameworks and their performance and will examine Coalesce as a solution that supports data operation principles and allows us to build automated, scalable, agile, well-documented data transformation pipelines on a cloud-based data platform.<br>

Publication Details

Journal
Figshare
Published
2024-10-11
DOI
https://doi.org/10.6084/m9.figshare.27214401
Primary Topic
Scientific Computing and Data Management
Type
article
Field-Weighted Citation Impact
0.00
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Accelerate Your Journey to a Modern Data Platform Using Coalesce

Figshare
Scientific Computing and Data Management
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Accelerate Your Journey to a Modern Data Platform Using Coalesce

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Abstract

Accelerate Your Journey to a Modern Data Platform Using Coalesce<b>Abstract </b>Most organizations face challenges while adapting to data platform modernization. The critical challenge that data platforms have faced is improving the scalability and performance of data processing due to the increased volume, variety, and velocity of data used for analytics.This article aims to summarize answers to the challenging questions of data platform modernization, and here are a few questions:How can we onboard new data sources with no code or less code?What steps are required to improve data integrity among various data source systems?How can CI/CD (continuous integration/continuous development) workflows across environments be simplified?How can we improve the testing process?How do we identify data quality issues early in the pipeline?As data platforms become more complex, managing them becomes difficult, and embracing the Data Operations principle is the way to address data operation challenges. We will look into the capabilities of ETL Frameworks and their performance and will examine Coalesce as a solution that supports data operation principles and allows us to build automated, scalable, agile, well-documented data transformation pipelines on a cloud-based data platform.<br>

Figshare
Industry, innovation and infrastructure
Openalex Percentile: Top 39%
Scientific Computing and Data Management
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