Knowledge Hut

NOVEMBER 27, 2023

Before being ready for processing, data goes through pre-processing which is a necessary group of operations that translate raw data into a more understandable format and thus, useful for further processing. Common processes are: Collect raw data and store it on a server.

Data Science 52

Data Science Datasets Machine Learning Portfolio 52

Rockset

DECEMBER 9, 2019

As a data engineer, my time is spent either moving data from one place to another, or preparing it for exposure to either reporting tools or front end users. As data collection and usage have become more sophisticated, the sources of data have become a lot more varied and disparate, volumes have grown and velocity has increased.

Data Engineer 40

Data Engineer Data Engineering Engineering Raw Data 40

U-Next

JUNE 29, 2022

Preparing data for analysis is known as extract, transform and load (ETL). While the ETL workflow is becoming obsolete, it still serves as a common word for the data preparation layers in a big data ecosystem. Working with large amounts of data necessitates more preparation than working with less data.

Big Data 40

Big Data Big Data Ecosystem Data Lake Raw Data 40

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 Relational Database AWS 52

AltexSoft

DECEMBER 21, 2021

.” In this article, you will find out what data labeling is, how it works, which data labeling types exist, and what best practices to follow to make this process smooth as glass. What is data labeling? A label or a tag is a descriptive element that tells a model what an individual data piece is so it can learn by example.

Machine Learning 52

Machine Learning Process Raw Data Datasets 52

U-Next

SEPTEMBER 28, 2022

HR Analytics collects and analyzes data that may help firms get essential insight into their operations. Data Collection . One of the first tasks in HR Analytics is to collect relevant data. Generally, the data needed to perform HR Analytics originates from the existing HR systems.

Recruitment 52

Recruitment Algorithm Machine Learning Utilities 52

AltexSoft

MAY 14, 2021

Big Data analytics processes and tools. Data ingestion. The process of identifying the sources and then getting Big Data varies from company to company. It’s worth noting though that data collection commonly happens in real-time or near real-time to ensure immediate processing. Apache Kafka.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

AUGUST 24, 2021

Within no time, most of them are either data scientists already or have set a clear goal to become one. Nevertheless, that is not the only job in the data world. And, out of these professions, this blog will discuss the data engineering job role. There are three stages in this real-world data engineering project.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

U-Next

SEPTEMBER 23, 2022

The fast development of digital technologies, IoT goods and connectivity platforms, social networking apps, video, audio, and geolocation services has created the potential for massive amounts of data to be collected/accumulated. Components of Database of the Big Data Ecosystem .

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

ProjectPro

SEPTEMBER 26, 2021

Big Data Engineers are professionals who handle large volumes of structured and unstructured data effectively. They are responsible for changing the design, development, and management of data pipelines while also managing the data sources for effective data collection.

Big Data 52

Big Data Data Engineer Data Engineering Engineering 52

ProjectPro

MAY 31, 2021

To build a big data project, you should always adhere to a clearly defined workflow. Before starting any big data project, it is essential to become familiar with the fundamental processes and steps involved, from gathering raw data to creating a machine learning model to its effective implementation.

Big Data 52

Big Data Coding Project Hadoop 52