Knowledge Hut

NOVEMBER 17, 2023

To provide end users with a variety of ready-made models, Azure Data engineers collaborate with Azure AI services built on top of Azure Cognitive Services APIs. Data engineers must therefore have a thorough understanding of programming languages like Python, Java, or Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

SEPTEMBER 26, 2023

We as Azure Data Engineers should have extensive knowledge of data modelling and ETL (extract, transform, load) procedures in addition to extensive expertise in creating and managing data pipelines, data lakes, and data warehouses. Using scripts, data engineers ought to be able to automate routine tasks.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

Generally, data pipelines are created to store data in a data warehouse or data lake or provide information directly to the machine learning model development. Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Databand.ai

DECEMBER 13, 2022

Bob also hosts The Engineering Side of Data podcast , which is dedicated to discussions around data engineering and features a variety of guests from the data engineering space. His specialties include Microsoft SQL Server, Azure Databricks, Azure Data Factory, SQL Server Integration Services (SSIS), and Azure Data Lake.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Edureka

FEBRUARY 9, 2023

Learn about popular ETL tools such as Xplenty, Stitch, Alooma, and others. To store various types of data, various methods are used. It is preferable to understand when to use a data lake versus a data warehouse to create data solutions for an organisation.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

AltexSoft

JUNE 26, 2023

Semi-structured data is not as strictly formatted as tabular one, yet it preserves identifiable elements — like tags and other markers — that simplify the search. They can be accumulated in NoSQL databases like MongoDB or Cassandra. Unstructured data represents up to 80-90 percent of the entire datasphere. No wonder only 0.5

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

NOVEMBER 14, 2015

Tools/Tech stack used: The tools and technologies used for such healthcare data management using Apache Hadoop are MapReduce and MongoDB. Objective and Summary of the project: With so much use of online applications the inflow of data has increased exponentially.

Hadoop 52

Hadoop Project Big Data Healthcare 52