Remove Business Intelligence Remove Data Lake Remove Data Pipeline Remove ETL Tools
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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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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. Let’s take a closer look.

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Data Pipeline- Definition, Architecture, Examples, and Use Cases

ProjectPro

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Table of Contents What is a Data Pipeline? The Importance of a Data Pipeline What is an ETL Data Pipeline?

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Are we ready to put AI in the hands of business users? by Caitlin Salt

Scott Logic

You can directly upload a data set, or it can come through some cort of ingestion pipeline using an ETL tool such as Amazon Glue. Predictive BI insights with Amazon QuickSight Amazon QuickSight is AWS’s offering in the business intelligence dashboard space.

BI 97
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Data Scientist vs Data Engineer: Differences and Why You Need Both

AltexSoft

They’re integral specialists in data science projects and cooperate with data scientists by backing up their algorithms with solid data pipelines. Juxtaposing data scientist vs engineer tasks. One data scientist usually needs two or three data engineers. Providing data access tools.

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15 ETL Project Ideas for Practice in 2023

ProjectPro

This indicates that more businesses will adopt the tools and methodologies useful in big data analytics, including implementing the ETL pipeline. Data engineers are in charge of developing data models, constructing data pipelines, and monitoring ETL (extract, transform, load).

Project 52
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Analytics Engineer: Job Description, Skills, and Responsibilities

AltexSoft

If we take the more traditional approach to data-related jobs used by larger companies, there are different specialists doing narrowly-focused tasks on different sides of the project. Data engineers build data pipelines and perform ETL — extract data from sources, transform it, and load it into a centralized repository like a data warehouse.