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Why thinking like a tech company is essential for your business’s survival

CIO

To thrive in todays business environment, companies must align their technological and cultural foundations with their ultimate goals. The phrase every company is a tech company gets thrown around a lot, but what does that actually mean? To us, its not just about using technology its about thinking like a tech company.

Company 186
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What is data architecture? A framework to manage data

CIO

Data architecture principles According to David Mariani , founder and CTO of semantic layer platform AtScale, six principles form the foundation of modern data architecture: View data as a shared asset. Provide user interfaces for consuming data. Scalable data pipelines. Seamless data integration.

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The key to operational AI: Modern data architecture

CIO

From customer service chatbots to marketing teams analyzing call center data, the majority of enterprises—about 90% according to recent data —have begun exploring AI. For companies investing in data science, realizing the return on these investments requires embedding AI deeply into business processes.

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Fundamentals of Data Engineering

Xebia

The following is a review of the book Fundamentals of Data Engineering by Joe Reis and Matt Housley, published by O’Reilly in June of 2022, and some takeaway lessons. This book is as good for a project manager or any other non-technical role as it is for a computer science student or a data engineer.

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Comprehensive data management for AI: The next-gen data management engine that will drive AI to new heights

CIO

The challenges of integrating data with AI workflows When I speak with our customers, the challenges they talk about involve integrating their data and their enterprise AI workflows. The core of their problem is applying AI technology to the data they already have, whether in the cloud, on their premises, or more likely both.

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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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Make the leap to Hybrid with Cloudera Data Engineering

Cloudera

When we introduced Cloudera Data Engineering (CDE) in the Public Cloud in 2020 it was a culmination of many years of working alongside companies as they deployed Apache Spark based ETL workloads at scale. Each unlocking value in the data engineering workflows enterprises can start taking advantage of.