Knowledge Hut

JANUARY 18, 2024

Data science is a multidisciplinary field that combines computer programming, statistics, and business knowledge to solve problems and make decisions based on data rather than intuition or gut instinct. It requires mathematical modeling, machine learning, and other advanced statistical methods to extract useful insights from raw data.

Data Science 52

Data Science Computer Science Programming Language NoSQL 52

Knowledge Hut

NOVEMBER 27, 2023

This is important because this will help you understand what areas to focus on while following the Data Science Learning Path. Is it the part where you turn raw data into useful ones, or it the part where you engineer new features out of the existing ones in order to help create suitable models?

Data Science 97

Data Science Healthcare Machine Learning Telecommunication 97

Knowledge Hut

OCTOBER 8, 2023

You must be proficient in NoSQL and SQL for data engineers to help with database management. Data pipeline design - It's where you extract raw data from different data sources and export it for analysis. Data engineers must design efficient pipelines for easy transfer of data.

AWS 52

AWS Data Engineering Data Engineer Engineering 52

Knowledge Hut

DECEMBER 29, 2023

Data and Statistical Analysis The process of cleaning, organizing, and translating raw data into information that can be used by organizations in order to make educated choices includes data analysis. It might also be industry-specific, such as the healthcare or financial industries, for example.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

DECEMBER 26, 2023

Businesses benefit at large with these data collection and analysis as they allow organizations to make predictions and give insights about products so that they can make informed decisions, backed by inferences from existing data, which, in turn, helps in huge profit returns to such businesses. What is the role of a Data Engineer?

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

Rockset

JULY 22, 2022

Last week, Rockset hosted a conversation with a few seasoned data architects and data practitioners steeped in NoSQL databases to talk about the current state of NoSQL in 2022 and how data teams should think about it. Data accessed together should all be in the same item or the same table or the same collection.

NoSQL 52

NoSQL SQL Database AWS 52

ProjectPro

JANUARY 31, 2023

Big data operations require specialized tools and techniques since a relational database cannot manage such a large amount of data. Big data enables businesses to gain a deeper understanding of their industry and helps them extract valuable information from the unstructured and raw data that is regularly collected.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

JULY 27, 2021

Data engineers and data scientists work very closely together, but there are some differences in their roles and responsibilities. Data Engineer Data scientist The primary role is to design and implement highly maintainable database management systems. How is a data architect different from a data engineer?

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

ProjectPro

AUGUST 16, 2021

Thanks to innovation and research in machine learning algorithms, we can seek knowledge and learn from insights that hide in the data. Data Engineers, Data Scientists, Data Architects have become significant job titles in the market, and the opportunities keep soaring.

Machine Learning 40

Machine Learning Coding Project Deep Learning 40

AltexSoft

MAY 12, 2023

Data lakes offer a flexible and cost-effective approach for managing and storing unstructured data, ensuring high durability and availability. Last but not least, you may need to leverage data labeling if you train models for custom tasks. Choose the right tools and platforms.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

MARCH 14, 2023

Data storage The tools mentioned in the previous section are instrumental in moving data to a centralized location for storage, usually, a cloud data warehouse, although data lakes are also a popular option. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59