Knowledge Hut

JANUARY 30, 2024

Whether it's aggregating customer interactions, analyzing historical sales trends, or processing real-time sensor data, data extraction initiates the process. Data Source Typically starts with unprocessed or poorly structured data sources. Primary Focus Structuring and preparing data for further analysis.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Knowledge Hut

JULY 26, 2023

This velocity aspect is particularly relevant in applications such as social media analytics, financial trading, and sensor data processing. Variety: Variety represents the diverse range of data types and formats encountered in Big Data. Handling this variety of data requires flexible data storage and processing methods.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

AltexSoft

AUGUST 29, 2023

Unlike traditional DWs, cloud data warehouses like Snowflake, BigQuery, and Redshift come pre-equipped with advanced features; learn more about the differences in our dedicated article. Unlike data warehouses, data lakes allow a schema-on-read approach, enabling greater flexibility in data storage.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Edureka

AUGUST 2, 2023

Organisations and businesses are flooded with enormous amounts of data in the digital era. This information is gathered from a variety of sources, including sensor readings, social media engagements, and client transactions. Raw data, however, is frequently disorganised, unstructured, and challenging to work with directly.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

AltexSoft

MAY 14, 2021

To understand Big Data, you need to get acquainted with its attributes known as the four V’s: Volume is what hides in the “big” part of Big Data. This relates to terabytes to petabytes of information coming from a range of sources such as IoT devices, social media, text files, business transactions, etc. Data cleansing.

Big Data 78

Big Data Data Analytics IT NoSQL 78

U-Next

AUGUST 11, 2022

A Data Scientist’s job entails deciphering and analyzing complex, unstructured data gathered from several sources. Read on to learn about the career opportunities and salary of a Data Scientist. The first step is capturing data, extracting it periodically, and adding it to the pipeline. Introduction.

Data Science 40

Data Science Data Cleanse Unstructured Data Machine Learning 40

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52