Remove Data Lakes Remove Data Quality Remove ETL Remove Tableau
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Essential data engineering tools for 2023: Empowering for management and analysis

Data Science Dojo

These tools provide data engineers with the necessary capabilities to efficiently extract, transform, and load (ETL) data, build data pipelines, and prepare data for analysis and consumption by other applications. It allows data engineers to define and manage complex workflows as directed acyclic graphs (DAGs).

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Deep Thoughts on Data Flow with Alation & Trifacta

Alation

Data lakes, while useful in helping you to capture all of your data, are only the first step in extracting the value of that data. Additionally, because of the collaborative features found in the Alation Data Catalog, you also gain the ability for data to be easily shared, used and reused.

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Top Data Analytics Skills and Platforms for 2023

ODSC - Open Data Science

Skills like effective verbal and written communication will help back up the numbers, while data visualization (specific frameworks in the next section) can help you tell a complete story. Data Wrangling: Data Quality, ETL, Databases, Big Data The modern data analyst is expected to be able to source and retrieve their own data for analysis.

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What are the Biggest Challenges with Migrating to Snowflake?

phData

Setting up the Information Architecture Setting up an information architecture during migration to Snowflake poses challenges due to the need to align existing data structures, types, and sources with Snowflake’s multi-cluster, multi-tier architecture. Moving historical data from a legacy system to Snowflake poses several challenges.

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