U-Next

MARCH 1, 2023

Let’s discuss some of the key responsibilities of a Data Engineer: Data Engineers are responsible for deploying the solutions they design and build, and they should have a good knowledge of cloud platforms like AWS, Azure, etc. Analyzing this data often involves Machine Learning, a part of Data Science.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Silectis

JANUARY 3, 2021

Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse. Cassandra A database built by the Apache Foundation.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Edureka

FEBRUARY 9, 2023

Data infrastructure, data warehousing, data mining, data modelling, and other tasks are all part of a company’s data science programme, and data engineers are in charge of the majority of them. Microsoft Azure is a modern cloud platform that provides a wide range of services to businesses.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

AltexSoft

JUNE 26, 2023

Relational vs non-relational databases As we mentioned above, relational or SQL databases are designed for structured or tabular data. Non-relational databases , on the other hand, work for data forms and structures other than tables. and its value (male, red, $100, etc.).

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

JANUARY 19, 2022

Data infrastructure, data warehousing, data mining, data modeling, etc., are part of a company's data science program, and data engineers handle most of these tasks. Microsoft Azure is a modern cloud platform that offers businesses a wide range of services.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

OCTOBER 8, 2021

Data integration defines the process of collecting data from a number of disparate source systems and presenting it in a unified form within a centralized location like a data warehouse. So, why is data integration such a big deal? On-premise data integration tools. Cloud-based data integration tools.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

AltexSoft

NOVEMBER 23, 2021

Nowadays, all organizations need real-time data to make instant business decisions and bring value to their customers faster. But this data is all over the place: It lives in the cloud, on social media platforms, in operational systems, and on websites, to name a few. Data virtualization vs data consolidation.

Process 69

Process Data Lake Metadata Data Warehouse 69