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How To Future-Proof Your Data Pipelines

Ascend.io

Why Future-Proofing Your Data Pipelines Matters Data has become the backbone of decision-making in businesses across the globe. The ability to harness and analyze data effectively can make or break a company’s competitive edge. Resilience and adaptability are the cornerstones of a future-proof data pipeline.

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Observability in Your Data Pipeline: A Practical Guide

Databand.ai

Observability in Your Data Pipeline: A Practical Guide Eitan Chazbani June 8, 2023 Achieving observability for data pipelines means that data engineers can monitor, analyze, and comprehend their data pipeline’s behavior. This is part of a series of articles about data observability.

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Data Engineer vs Data Analyst: Key Differences and Similarities

Knowledge Hut

They are specialists in database management systems, cloud computing, and ETL (Extract, Transform, Load) tools. Making sure that data is organized, structured, and available to other teams or apps is the main responsibility of a data engineer. Also, data analysts have a thorough comprehension of statistical ideas and methods.

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What is Data Orchestration?

Monte Carlo

Picture this: your data is scattered. Data pipelines originate in multiple places and terminate in various silos across your organization. Your data is inconsistent, ungoverned, inaccessible, and difficult to use. Some of the value companies can generate from data orchestration tools include: Faster time-to-insights.

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What’s Next for Data Engineering in 2023? 10 Predictions 

Monte Carlo

Prediction #5: Metrics Layers Unify Data Architectures (Tomasz) Tomasz’s next prediction dealt with the ascendance of the metrics layer, also known as the semantics layer. This made a big splash at dbt’s Coalesce the last two years and it’s going to start transforming the way data pipelines and data operations look.

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20+ Data Engineering Projects for Beginners with Source Code

ProjectPro

Data Sourcing: Building pipelines to source data from different company data warehouses is fundamental to the responsibilities of a data engineer. So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines.

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Top 25 Data Science Tools To Use in 2024

Knowledge Hut

With this tool, data science professionals can quickly extract and transform data. It allows integrating various data analysis & data-related components for machine learning (ML) and data mining objective by leveraging its modular data pipelining concept.