Knowledge Hut

MAY 9, 2024

While only 33% of job ads specifically demand a data science degree, the highly sought-after technical skills are SQL and Python. Data Architect ScyllaDB Data architects play a crucial role in designing an organization's data management framework by assessing data sources and integrating them into a centralized plan.

Data Science 52

Data Science Data Mining Data Architect Programming Language 52

Knowledge Hut

JULY 27, 2023

To ensure effective data processing and analytics for enterprises, work with data analysts, data scientists, and other stakeholders to optimize data storage and retrieval. Using the Hadoop framework, Hadoop developers create scalable, fault-tolerant Big Data applications. What do they do?

Hadoop 52

Hadoop Programming Language Banking Scala 52

Knowledge Hut

DECEMBER 21, 2023

Data engineering involves a lot of technical skills like Python, Java, and SQL (Structured Query Language). For a data engineer career, you must have knowledge of data storage and processing technologies like Hadoop, Spark, and NoSQL databases.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Knowledge Hut

DECEMBER 26, 2023

You can perform operations like adding, deleting, and extracting data from a database, carrying out analytical functions, and modification of database structures. NoSQL is a distributed data storage that is becoming increasingly popular. Some of NoSQL examples are Apache River, BaseX, Ignite, Hazelcast, Coherence, etc.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

JANUARY 31, 2023

There are three steps involved in the deployment of a big data model: Data Ingestion: This is the first step in deploying a big data model - Data ingestion, i.e., extracting data from multiple data sources. Data Processing: This is the final step in deploying a big data model.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Rockset

FEBRUARY 17, 2022

But our goal is not purely to move data from point A to point B, although that’s how I describe my job to most people. Our end goal is to create some form of a reliable, centralized, and easy-to-use data storage layer that can then be utilized by multiple teams. As data engineers, how we engineer said data is important.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52