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

AltexSoft

Data is now one of the most valuable assets for any kind of business. The 11th annual survey of Chief Data Officers (CDOs) and Chief Data and Analytics Officers reveals 82 percent of organizations are planning to increase their investments in data modernization in 2023. What is a data architect?

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Highest Paying Data Science Jobs in the World

Knowledge Hut

Data Science, with its interdisciplinary approach, combines statistics, computer science, and domain knowledge and has opened up a world of exciting and lucrative career opportunities for professionals with the right skills and expertise. The market is flooding with the highest paying data science jobs. What is Data Science?

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Top 16 Data Science Job Roles To Pursue in 2024

Knowledge Hut

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. Thus, almost every organization has access to large volumes of rich data and needs “experts” who can generate insights from this rich data.

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Data Engineering Learning Path: A Complete Roadmap

Knowledge Hut

Data engineers make a tangible difference with their presence in top-notch industries, especially in assisting data scientists in machine learning and deep learning. Let us understand here the complete big data engineer roadmap to lead a successful Data Engineering Learning Path.

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Top 16 Data Science Specializations of 2024 + Tips to Choose

Knowledge Hut

The market for analytics is flourishing, as is the usage of the phrase Data Science. 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.

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Is Learning Data Science Hard - A Complete Guide

Knowledge Hut

Data science is a multidisciplinary field that combines computer programming, statistics, and business knowledge to solve problems and make decisions based on data rather than intuition or gut instinct. It requires mathematical modeling, machine learning, and other advanced statistical methods to extract useful insights from raw data.

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Telecom Network Analytics: Transformation, Innovation, Automation

Cloudera

One of the most substantial big data workloads over the past fifteen years has been in the domain of telecom network analytics. The Dawn of Telco Big Data: 2007-2012. Suddenly, it was possible to build a data model of the network and create both a historical and predictive view of its behaviour.