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Python for Data Engineering

Ascend.io

Data engineers can find one for almost any need, from data extraction to complex transformations, ensuring that they’re not reinventing the wheel by writing code that’s already been written. Exceptional at data retrieval and manipulation within RDBMS. It's specialized for database querying.

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?Data Engineer vs Machine Learning Engineer: What to Choose?

Knowledge Hut

Skills A data engineer should have good programming and analytical skills with big data knowledge. Examples Pull daily tweets from the data warehouse hive spreading in multiple clusters. The generalist position would suit a data scientist looking for a transition into a data engineer.

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97 things every data engineer should know

Grouparoo

39 How to Prevent a Data Mutiny Key trends: modular architecture, declarative configuration, automated systems 40 Know the Value per Byte of Your Data Check if you are actually using your data 41 Know Your Latencies key questions: how old is data? 71 The Hidden Cost of Data Input/Output Storage choices impact performance.

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Recap of Hadoop News for September

ProjectPro

News on Hadoop-September 2016 HPE adapts Vertica analytical database to world with Hadoop, Spark.TechTarget.com,September 1, 2016. To compete in a field of diverse data tools, Vertica 8.0 has expanded its analytical database support for Apache Hadoop and Spark integration and also to enhance Apache Kafka management pipeline.

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Solutions Architect Job Roles in 2024 [Career Options]

Knowledge Hut

Data Solutions Architect Role Overview: Design and implement data management, storage, and analytics solutions to meet business requirements and enable data-driven decision-making. Role Level: Mid to senior-level position requiring expertise in data architecture, database technologies, and analytics platforms.

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Accenture’s Smart Data Transition Toolkit Now Available for Cloudera Data Platform

Cloudera

The client decided to migrate away from their relational database-centric Enterprise Data Warehouse as an ingestion and data processing platform after the maintenance costs, limited flexibility, and growth of the RDBMS platform became unsustainable with the increased complexity of the client’s data footprint.

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What is Real-time Data Ingestion? Use cases, Tools, Infrastructure

Knowledge Hut

Studying data in deeper detail can help to identify the inefficiencies, bottlenecks or anomalies hence leading to quick actions resulting in efficient operations and reduced costs. Appreciated Customer Experience: The industry focuses on customer-centric approaches to enhance the overall customer experience.