Knowledge Hut

DECEMBER 26, 2023

They use technologies like Storm or Spark, HDFS, MapReduce, Query Tools like Pig, Hive, and Impala, and NoSQL Databases like MongoDB, Cassandra, and HBase. They also make use of ETL tools, messaging systems like Kafka, and Big Data Tool kits such as SparkML and Mahout.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

Knowledge Hut

NOVEMBER 17, 2023

Azure Services You must be well-versed in a variety of Azure services, including Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Analysis Services, Azure Stream Analytics, and Azure Data Lake Storage, in order to succeed as an Azure Data Engineer.

Data Engineer 52

Data Engineer Data Engineering Engineering Scala 52

Edureka

FEBRUARY 9, 2023

A data engineer should be familiar with popular Big Data tools and technologies such as Hadoop, MongoDB, and Kafka. Because companies are increasingly replacing physical servers with cloud services, data engineers must understand cloud storage and cloud computing.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Mining 52

Knowledge Hut

SEPTEMBER 26, 2023

To ascertain and address data requirements, they engage with business stakeholders. In order to satisfy company demands, they are also in charge of administering, overseeing, and guaranteeing data security and privacy. Data engineers handle vast volumes of data on a regular basis and don't only deal with normal data.

Certification 52

Certification Data Engineer Data Engineering Engineering 52

Knowledge Hut

SEPTEMBER 6, 2023

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.

Big Data 52

Big Data Certification Hadoop Kafka 52

Knowledge Hut

JUNE 23, 2023

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. You can also post your work on your LinkedIn profile.

Data Engineer 52

Data Engineer Data Engineering Engineering NoSQL 52

ProjectPro

JANUARY 19, 2022

Data engineers don't just work with conventional data; and they're often entrusted with handling large amounts of data. Hadoop, MongoDB, and Kafka are popular Big Data tools and technologies a data engineer needs to be familiar with. They need to come up with ideas and put them into action.

Data Engineer 52

Data Engineer Data Engineering Engineering Data Storage 52