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. What are the Data Engineer Career Opportunities?

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Data Engineering Podcast

JUNE 11, 2021

Summary Google pioneered an impressive number of the architectural underpinnings of the broader big data ecosystem. Now they offer the technologies that they run internally to external users of their cloud platform. Now they offer the technologies that they run internally to external users of their cloud platform.

Google Cloud 100

Google Cloud Cloud Big Data Ecosystem BI 100

Edureka

JUNE 1, 2023

In today’s digital era, businesses operate in a data-driven environment where data is generated at an unprecedented rate. Every single activity of our daily life is influenced by connected existence and nowadays all these activities include technology. Majority of these data is stored in the cloud.

AWS 52

AWS Data Analytics Cloud Amazon Web Services 52

U-Next

SEPTEMBER 23, 2022

Concepts such as components of databases and other attributes related to Data Science have taken the world by storm. To handle this large amount of data, we want a far more complicated architecture comprised of numerous components of the database performing various tasks rather than just one. . Apple is one such technology.

Big Data Ecosystem 40

Big Data Ecosystem Big Data Healthcare Data Lake 40

AltexSoft

JUNE 26, 2023

While today’s world abounds with data, gathering valuable information presents a lot of organizational and technical challenges, which we are going to address in this article. We’ll particularly explore data collection approaches and tools for analytics and machine learning projects. What is data collection?

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

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

MAY 23, 2015

2014 Kaggle Competition Walmart Recruiting – Predicting Store Sales using Historical Data Description of Walmart Dataset for Predicting Store Sales What kind of big data and hadoop projects you can work with using Walmart Dataset? petabytes of unstructured data from 1 million customers every hour. Inkiru Inc.

Big Data 52

Big Data Data Analysis Hadoop Retail 52

ProjectPro

FEBRUARY 8, 2017

.” said the McKinsey Global Institute (MGI) in its executive overview of last month's report: "The Age of Analytics: Competing in a Data-Driven World." 2016 was an exciting year for big data with organizations developing real-world solutions with big data analytics making a major impact on their bottom line.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

ProjectPro

DECEMBER 28, 2021

Data analytics also helps organizations understand their customers better, narrow down their target audiences, and improve marketing campaigns. For example, a pervasive trend identified by IBM's Global Technology Outlook 2015 is that 60% of valuable sensory data can be squandered within milliseconds if not acted!

Architecture 52

Architecture Kafka Java Scala 52

ProjectPro

JUNE 4, 2015

Big data applications using Apache Hadoop continue to run even if any of the individual cluster or server fails owing to the robust and stable nature of Hadoop. Table of Contents Big Data Hadoop Training Videos- What is Hadoop and its popular vendors? Image Credit: slidehshare.net Key Benefits of Hadoop 2.0

Hadoop 52

Hadoop Architecture IT Java 52