ProjectPro

FEBRUARY 21, 2023

Due to the enormous amount of data being generated and used in recent years, there is a high demand for data professionals, such as data engineers, who can perform tasks such as data management, data analysis, data preparation, etc. big data and ETL tools, etc. PREVIOUS NEXT <

Certification 52

Certification Data Engineering Data Engineer Engineering 52

AltexSoft

OCTOBER 30, 2021

A data scientist takes part in almost all stages of a machine learning project by making important decisions and configuring the model. Data preparation and cleaning. Final analytics are only as good and accurate as the data they use. An overview of data engineer skills. Deploying machine learning models.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

ProjectPro

JANUARY 19, 2022

Data engineers must thoroughly understand programming languages such as Python, Java, or Scala. Relational and non-relational databases are among the most common data storage methods. ETL (extract, transform, and load) techniques move data from databases and other systems into a single hub, such as a data warehouse.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Edureka

JULY 4, 2024

On the other hand, thanks to the Spark component, you can perform data preparation, data engineering, ETL, and machine learning tasks using industry-standard Apache Spark. The platform’s massive parallel processing (MPP) architecture empowers you with high-performance querying of even massive datasets.

Data Lake 40

Data Lake Pipeline-centric Scala Data Warehouse 40

AltexSoft

MARCH 30, 2023

Source: The Data Team’s Guide to the Databricks Lakehouse Platform Integrating with Apache Spark and other analytics engines, Delta Lake supports both batch and stream data processing. Besides that, it’s fully compatible with various data ingestion and ETL tools.

Scala 64

Scala Data Lake BI Google Cloud 64