Remove Business Intelligence Remove Data Warehouse Remove ETL Tools Remove Metadata
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Modern Data Engineering

Towards Data Science

I’d like to discuss some popular Data engineering questions: Modern data engineering (DE). Does your DE work well enough to fuel advanced data pipelines and Business intelligence (BI)? Are your data pipelines efficient? Often it is a data warehouse solution (DWH) in the central part of our infrastructure.

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Moving Past ETL and ELT: Understanding the EtLT Approach

Ascend.io

Secondly , the rise of data lakes that catalyzed the transition from ELT to ELT and paved the way for niche paradigms such as Reverse ETL and Zero-ETL. Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

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The Rise of the Data Engineer

Maxime Beauchemin

I joined Facebook in 2011 as a business intelligence engineer. By the time I left in 2013, I was a data engineer. Instead, Facebook came to realize that the work we were doing transcended classic business intelligence. Let’s highlight the fact that the abstractions exposed by traditional ETL tools are off-target.

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An Introduction To Data And Analytics Engineering For Non-Programmers

Data Engineering Podcast

Summary Applications of data have grown well beyond the venerable business intelligence dashboards that organizations have relied on for decades. You can observe your pipelines with built in metadata search and column level lineage. You can observe your pipelines with built in metadata search and column level lineage.

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Data Lake Explained: A Comprehensive Guide to Its Architecture and Use Cases

AltexSoft

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data.

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Data Scientist vs Data Engineer: Differences and Why You Need Both

AltexSoft

Such visualizations as graphs and charts are typically prepared by data analysts or business analysts, though not every project has those people employed. Then, a data scientist uses complex business intelligence tools to present business insights to executives. Managing data and metadata.

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The Good and the Bad of Databricks Lakehouse Platform

AltexSoft

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

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