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

ProjectPro

JANUARY 19, 2022

Good knowledge of various machine learning and deep learning algorithms will be a bonus. Knowledge of popular big data tools like Apache Spark, Apache Hadoop, etc. Good communication skills as a data engineer directly works with the different teams.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Knowledge Hut

JUNE 23, 2023

Data engineers make a tangible difference with their presence in top-notch industries, especially in assisting data scientists in machine learning and deep learning. You should have the expertise to collect data, conduct research, create models, and identify patterns.

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

ProjectPro

AUGUST 24, 2021

So, work on projects that guide you on how to build end-to-end ETL/ELT data pipelines. Big Data Tools: Without learning about popular big data tools, it is almost impossible to complete any task in data engineering. Ability to adapt to new big data tools and technologies.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Databand.ai

DECEMBER 13, 2022

In fact, he has experience in almost all aspects of the data life cycle, from dashboards, analytics, and statistical tests to setting up servers, building machine learning pipelines, and data warehouses. Furthermore, he is experienced in most types of datasets having built deep learning models in NLP, CV, and RL tasks.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

AltexSoft

JUNE 26, 2023

It requires a lot of storage space and advanced, compute-intensive machine learning techniques like natural language processing (NLP) or image recognition for processing. Read our articles on structured vs unstructured data and unstructured data to learn more. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

AUGUST 21, 2015

i) Data Ingestion – The foremost step in deploying big data solutions is to extract data from different sources which could be an Enterprise Resource Planning System like SAP, any CRM like Salesforce or Siebel , RDBMS like MySQL or Oracle, or could be the log files, flat files, documents, images, social media feeds.

Hadoop 40

Hadoop Big Data Metadata Java 40