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Top 16 Data Science Job Roles To Pursue in 2024

Knowledge Hut

In other words, they develop, maintain, and test Big Data solutions. They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase. Statistician A Statistician has the responsibility of getting useful insights from data.

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

AltexSoft

If KPI goals are not met, a data architect recommends solutions (including new technologies) to improve the existing framework. Besides, it’s up to this specialist to guarantee compliance with laws, regulations, and standards related to data.

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Data Engineering Learning Path: A Complete Roadmap

Knowledge Hut

Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala. You should be thorough with technicalities related to relational and non-relational databases, Data security, ETL (extract, transform, and load) systems, Data storage, automation and scripting, big data tools, and machine learning.

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Top 20+ Big Data Certifications and Courses in 2023

Knowledge Hut

Problem-Solving Abilities: Many certification courses provide projects and assessments which require hands-on practice of big data tools which enhances your problem solving capabilities. Networking Opportunities: While pursuing big data certification course you are likely to interact with trainers and other data professionals.

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Top 10 Big Data Companies of 2023

Knowledge Hut

Through visualizations, machine learning models, and predictive analytics, the company's cloud platform assists businesses in making data meaningful. SAPC The HANA-in memory SQL server is the SAPC's primary big data tool; however, it also offers several analytics tools.

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How to Become an Azure Data Engineer in 2023?

ProjectPro

Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with. Companies are increasingly substituting physical servers with cloud services, so data engineers need to know about cloud storage and cloud computing.

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The Top 25 Data Engineering Influencers and Content Creators on LinkedIn

Databand.ai

Deepanshu’s skills include SQL, data engineering, Apache Spark, ETL, pipelining, Python, and NoSQL, and he has worked on all three major cloud platforms (Google Cloud Platform, Azure, and AWS). He also shares his thoughts on LinkedIn as a regular contributor around topics like AWS, data analytics, and data engineering.