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What is Data Engineering: Explaining Data Pipeline, Data Warehouse, and Data Engineer Role

Altexsoft

If we look at the hierarchy of needs in data science implementations, we’ll see that the next step after gathering your data for analysis is data engineering. This discipline is not to be underestimated, as it enables effective data storing and reliable data flow while taking charge of the infrastructure.

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5 hot IT budget investments — and 2 going cold

CIO

Upgrading cloud infrastructure is critical for deploying broad AI initiatives more quickly, so that’s a key area where investments are being made this year. Besides surgery, the hospital is also investing in robotics for the transportation and delivery of medications.

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Hire Big Data Engineer: Salaries, Stack and Roles

Mobilunity

Technologies that have expanded Big Data possibilities even further are cloud computing and graph databases. The cloud offers excellent scalability, while graph databases offer the ability to display incredible amounts of data in a way that makes analytics efficient and effective. Who is Big Data Engineer?

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Unlocking the Power of AI with a Real-Time Data Strategy

CIO

Supply chain With companies trying to stay lean with just-in-time practices, it’s important to understand real-time market conditions, delays in transportation, and raw supply delays, and adjust for them as the conditions are unfolding. Cloud-native apps, microservices and mobile apps drive revenue with their real-time customer interactions.

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Data Migration: Process, Types, and Golden Rules to Know

Altexsoft

Otherwise, let’s start from the most basic question: What is data migration? What is data migration? In general terms, data migration is the transfer of the existing historical data to new storage, system, or file format. Usually, data migration comes as a part of a larger project such as. Storage migration.

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ETL vs ELT: Key Differences Everyone Must Know

Altexsoft

With ETL, data is transformed in a temporary staging area before it gets to a target repository (e.g an enterprise data warehouse ) whereas ELT makes it possible to transform data after it got loaded into a target system (cloud data warehouses or data lakes ). It doesn’t provide data lake support.

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The Good and the Bad of Hadoop Big Data Framework

Altexsoft

Apache Hadoop is an open-source Java-based framework that relies on parallel processing and distributed storage for analyzing massive datasets. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics. What is Hadoop? Apache Hadoop architecture.