Knowledge Hut

DECEMBER 26, 2023

The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications. In other words, they develop, maintain, and test Big Data solutions.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer is someone proficient in a variety of programming languages and frameworks, such as Python, SQL, Scala, Hadoop, Spark, etc. One of the primary focuses of a Data Engineer's work is on the Hadoop data lakes. NoSQL databases are often implemented as a component of data pipelines.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

DECEMBER 26, 2023

After carefully exploring what we mean when we say "big data," the book explores each phase of the big data lifecycle. With Tableau, which focuses on big data visualization , you can create scatter plots, histograms, bar, line, and pie charts.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

Knowledge Hut

MARCH 27, 2024

MongoDB This free, open-source platform, which came into the limelight in 2010, is a document-oriented (NoSQL) database that is used to store a large amount of information in a structured manner. Although it's open source, it only supports 10000 data rows and one logical processor. are accessible via URL.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

AltexSoft

JULY 27, 2021

This type of CF uses machine learning or data mining techniques to build a model to predict a user’s reaction to items. Google singles out four key phases through which a recommender system processes data. They are information collection, storing, analysis, and filtering. Data collection. Model-based.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76