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Top 16 Data Science Specializations of 2024 + Tips to Choose

Knowledge Hut

Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization. A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse.

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Data Architect: Role Description, Skills, Certifications and When to Hire

AltexSoft

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

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Recap of Hadoop News for January 2018

ProjectPro

will more likely be used as a data tiering strategy where data will be stored on cheaper and slower media. Source : [link] 6 Key Future Prospects of Big Data Analytics in Healthcare Market for Forecast Period 2017 - 2026. CRM will remain the go-to tool for big data analytics in healthcare market.

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Is Azure Data Engineer Certification (DP-203) Worth It?

Knowledge Hut

What is Microsoft Azure Data Engineer Certification? The Azure Data Engineering Certificate is designed for data engineers and developers who wish to show that they are experts at creating and implementing data solutions using Microsoft Azure data services.

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The DataOps Vendor Landscape, 2021

DataKitchen

Seldon — Streamlines the data science workflow, with audit trails, advanced experiments, continuous integration, and deployment. Metis Machine — Enterprise-scale Machine Learning and Deep Learning deployment and automation platform for rapid deployment of models into existing infrastructure and applications.

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20 Solved End-to-End Big Data Projects with Source Code

ProjectPro

A big data project is a data analysis project that uses machine learning algorithms and different data analytics techniques on a large dataset for several purposes, including predictive modeling and other advanced analytics applications. Concepts of deep learning can be used to analyze this dataset properly.