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Market Analysis Report

Architecting and Automating Data Pipelines

A Guide to Efficient Data Engineering for BI and Data Science

Explosive growth in data volumes, users, and use cases causes pain for all data stakeholders, and especially for architects and data engineers. Demand for analytics-ready data far outstrips the capacity of data engineering groups to build and support data pipelines. This data supply-and-demand imbalance creates pressures for everyone who works with data, and creates a multitude of data management challenges.

Well-architected data pipelines lead to marked improvements in data access, analytics value, data engineer and data analyst productivity, and ability to adapt to changing business, regulatory, and technical environments.

Learn from analysts at global market research firm, Eckerson Group, how to set up a process for designing data pipelines that drives reuse and consistency; is output-driven for those who need data; avoids becoming “shelfware” ; and enables data users to produce reliable data pipelines at high speed and with minimum manual effort.

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