Knowledge Hut

DECEMBER 26, 2023

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. Data scientists work on deploying algorithms to the prepared data by the data engineers.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

WeCloudData

OCTOBER 19, 2021

Methodology In order to meet the technical requirements for recommender system development as well as other emerging data needs, the client has built a mature data pipeline through the use of cloud platforms like AWS in order to store user clickstream data, and Databricks in order to process the raw data.

Consulting 52

Consulting Systems NoSQL Raw Data 52

WeCloudData

OCTOBER 19, 2021

Methodology In order to meet the technical requirements for recommender system development as well as other emerging data needs, the client has built a mature data pipeline through the use of cloud platforms like AWS in order to store user clickstream data, and Databricks in order to process the raw data.

Consulting 52

Consulting Systems NoSQL Raw Data 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. Other Competencies You should have proficiency in coding languages like SQL, NoSQL, Python, Java, R, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Non-relational Database 52

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 20, 2023

Skills A data engineer should have good programming and analytical skills with big data knowledge. A machine learning engineer should know deep learning, scaling on the cloud, working with APIs, etc. Examples Pull daily tweets from the data warehouse hive spreading in multiple clusters.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87