2010 Big Data Data Storage Unstructured Data 
Knowledge Hut
MARCH 27, 2024
You can check out the Big Data Certification Online to have an in-depth idea about big data tools and technologies to prepare for a job in the domain. To get your business in the direction you want, you need to choose the right tools for big data analysis based on your business goals, needs, and variety.
Monte Carlo
MAY 14, 2024
Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.
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Knowledge Hut
NOVEMBER 7, 2023
The applications of cloud computing in businesses of all sizes, types, and industries for a wide range of applications, including data backup, email, disaster recovery, virtual desktops big data analytics, software development and testing, and customer-facing web apps. Knowledge of database query languages is required for this.
AltexSoft
AUGUST 29, 2023
In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Who needs a data lake?
ProjectPro
MARCH 14, 2014
The next decade of industries will be using Big Data to solve the unsolved data problems in the physical world. Big Data analysis will be about building systems around the data that is generated. Image Credit : hortonworks As per big data industry trends , the hype of Big Data had just begun in 2011.
AltexSoft
SEPTEMBER 21, 2023
In this edition of “The Good and The Bad” series, we’ll dig deep into Elasticsearch — breaking down its functionalities, advantages, and limitations to help you decide if it’s the right tool for your data-driven aspirations. As a result, Elasticsearch is exceptionally efficient in managing structured and unstructured data.
ProjectPro
JUNE 4, 2015
The basic principle of working behind Apache Hadoop is to break up unstructured data and distribute it into many parts for concurrent data analysis. 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.
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