Knowledge Hut

APRIL 3, 2023

The field of Backend Development is constantly evolving, and staying up-to-date with the latest tools and technologies is crucial for success. Backend developers work with programming languages such as Java, Python, Ruby, and PHP, as well as databases such as MySQL, MongoDB, and PostgreSQL. Experience working with databases and APIs.

Programming Language 52

Programming Language Computer Science Portfolio PostgreSQL 52

Knowledge Hut

JUNE 20, 2023

Let's find out the differences between a data scientist and a machine learning engineer below to make an informative decision. Data Engineer vs Machine Learning Engineer While there are similarities between a data engineer and a machine learning engineer, both play a key role in the technological world.

Machine Learning 52

Machine Learning Data Engineering Data Engineer Engineering 52

ProjectPro

APRIL 17, 2015

“Any sufficiently advanced technology is indistinguishable from magic.”– Big data technologies and practices are gaining traction and moving at a fast pace with novel innovations happening in this space. Big data analytics is making waves in every industry sector with novel tools and technology trends.

Big Data 52

Big Data Data Analysis NoSQL Deep Learning 52

U-Next

AUGUST 25, 2022

An open-spurce NoSQL database management program, MongoDB architecture, is used as an alternative to traditional RDMS. MongoDB is built to fulfil the needs of modern apps, with a technical base that allows you through: The document data model demonstrates the most effective approach to work with data. Introduction.

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

Databand.ai

DECEMBER 13, 2022

Currently, he helps companies define data-driven architecture and build robust data platforms in the cloud to scale their business using Microsoft Azure. On LinkedIn, he focuses largely on Spark, Hadoop, big data, big data engineering, and data engineering.

Data Engineering 52

Data Engineering Data Engineer Engineering AWS 52

Rockset

JUNE 7, 2022

On the other hand, non-relational databases (commonly referred to as NoSQL databases) are flexible databases for big data and real-time web applications. These databases were born out of necessity for storing large amounts of unstructured data. There are many NoSQL databases available in the market.

MongoDB 52

MongoDB NoSQL Non-relational Database Relational Database 52

ProjectPro

MAY 19, 2015

The requirement for processing zettabytes of unstructured big data is generating demand for professionals with Hadoop skills to work with unstructured data. Thus, professionals must learn Hadoop to ramp up on the big data technology as Hadoop is soon going to be identified as a must have skill by all big data companies.

Hadoop 40

Hadoop Big Data NoSQL Database-centric 40

ProjectPro

NOVEMBER 14, 2015

As we step into the latter half of the present decade, we can’t help but notice the way Big Data has entered all crucial technology-powered domains such as banking and financial services, telecom, manufacturing, information technology, operations, and logistics. That is where Apache Hadoop and Apache Spark come in.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

MARCH 27, 2024

Data tracking is becoming more and more important as technology evolves. A global data explosion is generating almost 2.5 quintillion bytes of data today, and unless that data is organized properly, it is useless. Some open-source technology for big data analytics are : Hadoop. Apache Spark.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

SEPTEMBER 6, 2023

Over the past decade, the IT world transformed with a data revolution. The rise of big data and NoSQL changed the game. Systems evolved from simple to complex, and we had to split how we find data from where we store it. Skills acquired : Core data concepts. Data storage options. Now, it's different.

Database 52

Database Certification MongoDB MySQL 52

DareData

JANUARY 30, 2023

They can be simple or complex, and they can involve multiple steps, technologies or formats such as CSV, Tabular or JSON formats. For data scientists, these skills are extremely helpful when it comes to manage and build more optimized data transformation processes, helping models achieve better speed and relability when set in production.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

ProjectPro

NOVEMBER 5, 2014

MongoDB NoSQL database is used in the big data stack for storing and retrieving one item at a time from large datasets whereas Hadoop is used for processing these large data sets. For organizations to keep the load off MongoDB in the production database, data processing is offloaded to Apache Hadoop.

MongoDB 40

MongoDB Hadoop NoSQL Big Data 40

ProjectPro

MARCH 19, 2015

Big Data NoSQL databases were pioneered by top internet companies like Amazon, Google, LinkedIn and Facebook to overcome the drawbacks of RDBMS. RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data.

NoSQL 49

NoSQL Big Data SQL Database-centric 49

Edureka

JANUARY 18, 2024

This guide provides a comprehensive understanding of the essential skills and knowledge required to become a successful data scientist, covering data manipulation, programming, mathematics, big data, deep learning, and machine learning technologies. Table of Contents Introduction to Data Science What is Data Science?

Data Science 40

Data Science Deep Learning NoSQL Machine Learning 40

AltexSoft

JUNE 26, 2023

Find sources of relevant data. Choose data collection methods and tools. Decide on a sufficient data amount. Set up data storage technology. Below, we’ll elaborate on each step one by one and share our experience of data collection. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

NOVEMBER 7, 2023

With quick access to various technologies through the cloud, you can develop more quickly and create almost anything you can imagine. You can swiftly provision infrastructure services like computation, storage, and databases, as well as machine learning, the internet of things, data lakes and analytics, and much more.

Cloud Computing 98

Cloud Computing Cloud Amazon Web Services Entertainment 98

AltexSoft

MAY 14, 2021

The concept of Big Data isn’t new: It has been the desired fruit for several decades already as the capabilities of software and hardware have made it possible for companies to successfully manage vast amounts of complex data. To make sense of the huge amounts of data, there are several techniques and practices. NoSQL databases.

Big Data 78

Big Data Data Analytics IT NoSQL 78

ProjectPro

JANUARY 19, 2022

As a result, the role of data engineer has become increasingly important in the technology industry. Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments. Data engineers will be in high demand as long as there is data to process. According to the 2020 U.S.

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

AltexSoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. The Hadoop toy. Fault tolerance.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Knowledge Hut

DECEMBER 27, 2023

Many business owners and professionals are interested in harnessing the power locked in Big Data using Hadoop often pursue Big Data and Hadoop Training. What is Big Data? Big data is often denoted as three V’s: Volume, Variety and Velocity. Ecommerce businesses like Alibaba, Amazon use big data in a massive way.

Big Data Tools 59

Big Data Tools Big Data Hadoop Database-centric 59

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop AWS Relational Database 52

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

OCTOBER 28, 2015

Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., and Flume in Hadoop is used to sources data which is stored in various sources like and deals mostly with unstructured data. The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

ProjectPro

JULY 30, 2021

Companies need engineers that can help them transition over to Cloud Computing or senior engineers who can maintain and innovate on the already established Cloud Computing technology. Building data storage and computing architecture locally were getting more expensive during the advent of Big Data technologies.

Cloud Computing 40

Cloud Computing Cloud Amazon Web Services AWS 40

AltexSoft

NOVEMBER 23, 2021

Multiple BI tools require access to the same data sources. Let’s take a look at real-world use cases to see how companies operating in different industries leverage data virtualization technology. Data virtualization platforms can link to different data sources including.

Process 69

Process Data Lake Metadata Data Warehouse 69

ProjectPro

JULY 27, 2021

This blog is your one-stop solution for the top 100+ Data Engineer Interview Questions and Answers. In this blog, we have collated the frequently asked data engineer interview questions based on tools and technologies that are highly useful for a data engineer in the Big Data industry.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40