Knowledge Hut

DECEMBER 21, 2023

In this article, we will discuss the 10 most popular Hadoop tools which can ease the process of performing complex data transformations. It incorporates several analytical tools that help improve the data analytics process. With the help of these tools, analysts can discover new insights into the data. What is Hadoop?

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

NOVEMBER 3, 2023

The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. Let us see where MongoDB for Data Science can help you.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

U-Next

MARCH 1, 2023

A solid understanding of relational databases and SQL language is a must-have skill, as an ability to manipulate large amounts of data effectively. A good Data Engineer will also have experience working with NoSQL solutions such as MongoDB or Cassandra, while knowledge of Hadoop or Spark would be beneficial.

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

Grouparoo

DECEMBER 26, 2021

They provide a method for storing information in an organized manner that ensures it remains accessible while providing the mechanisms to protect the integrity, confidentiality, and availability of the information they hold. There are many kinds of databases available, each with its strengths and weaknesses.

Database 52

Database NoSQL Relational Database Data Storage 52

Knowledge Hut

DECEMBER 26, 2023

According to the Cybercrime Magazine, the global data storage is projected to be 200+ zettabytes (1 zettabyte = 10 12 gigabytes) by 2025, including the data stored on the cloud, personal devices, and public and private IT infrastructures. In other words, they develop, maintain, and test Big Data solutions.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

Edureka

FEBRUARY 8, 2024

Whether you are hosting a website, running complex data analytics, or deploying machine learning models, the instance type serves as the foundation upon which your entire AWS architecture is built. In-Memory Caching- Memory-optimized instances are suitable for in-memory caching solutions, enhancing the speed of data access.

AWS 52

AWS NoSQL Deep Learning Datasets 52

AltexSoft

JUNE 26, 2023

All successful companies do it: constantly collect data. 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. Data collection as the first step in the decision-making process, driven by machine learning.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

ProjectPro

AUGUST 24, 2016

The NOSQL column oriented database has experienced incredible popularity in the last few years. HBase is a NoSQL , column oriented database built on top of hadoop to overcome the drawbacks of HDFS as it allows fast random writes and reads in an optimized way. . If you need random access, you have to have HBase."-

Architecture 40

Architecture IT Hadoop NoSQL 40

AltexSoft

JUNE 7, 2021

They both enable you to deal with huge collections of data no matter its format — from Excel tables to user feedback on websites to images and video files. As a result, a Big Data analytics task is split up, with each machine performing its own little part in parallel. You don’t need to archive or clean data before loading.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Knowledge Hut

MARCH 27, 2024

These are the situations where having a lot of data stored in one location and being able to access it quickly are necessary. What is a Data Structure? Using a data structure allows you to efficiently arrange data on a computer. Supports complex query relationships and ensures data integrity.

Database 52

Database Algorithm Relational Database PostgreSQL 52

Rockset

DECEMBER 31, 2022

Instead, databases such as DynamoDB have been designed to manage the new influx of data. DynamoDB is an Amazon Web Services database system that supports data structures and key-valued cloud services. Access to control rules As data gets more specific and personal, it becomes more important to have effective access control.

Non-relational Database 52

Non-relational Database Healthcare Amazon Web Services NoSQL 52

Knowledge Hut

APRIL 25, 2023

The tremendous growth in data generation, then the rise in data engineer jobs - there’s no arguing the fact that the big data industry is at its best pace and you, as an aspiring data engineer, have a lot to learn and make out of it - including some tools! While they go about it - enter big data data engineer tools.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Edureka

FEBRUARY 7, 2023

When it comes to professionals, data engineers are the most in-demand in the IT industry. Most students are already preparing to become skilled data engineers, and we are here to cover some of the most frequently asked topics in Azure Data Engineering Interview Questions. 2) What is Azure’s primary ETL service?

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

ProjectPro

DECEMBER 17, 2021

The companies are churning out massive volumes of data every day for analysis and deriving business insights. All this data is stored in a database that requires SQL-based queries for retrieval and transformations, making it essential for every data professional to learn SQL for data science and machine learning.

Data Science 52

Data Science SQL NoSQL Programming Language 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. Let's check some of the best big data analytics tools and free big data analytics tools.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Knowledge Hut

DECEMBER 13, 2023

Next-generation artificial intelligence and significant advancements in data mining and predictive analytics tools are driving the continued rapid expansion of big data software. The data is the property of various organizations, each of which uses it for various objectives. The USA serves as the company's home base.

Big Data 52

Big Data Consulting Hadoop Amazon Web Services 52

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). While functional, our current setup for managing tables is fragmented.

Big Data 78

Big Data Data Management Management Metadata 78

ProjectPro

JANUARY 31, 2023

Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Big data analytics analyzes structured and unstructured data to generate meaningful insights based on changing market trends, hidden patterns, and correlations. RDBMS stores structured data.

Big Data 52

Big Data Hadoop AWS Relational Database 52

Rockset

JULY 28, 2022

MongoDB has grown from a basic JSON key-value store to one of the most popular NoSQL database solutions in use today. This can be used to create data lakes, populate data warehouses or for specific use cases like offloading analytics and text search. Generally, this means your applications would submit new data to a queue.

MongoDB 52

MongoDB Kafka NoSQL Data Lake 52

ProjectPro

SEPTEMBER 9, 2021

Apache Hive and Apache Spark are the two popular Big Data tools available for complex data processing. To effectively utilize the Big Data tools, it is essential to understand the features and capabilities of the tools. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Ascend.io

NOVEMBER 21, 2023

Yet, looking into the complexities of today’s data-driven world, it becomes clear that ELT, while transformative at its inception, now forms just a part of an ever-evolving data landscape. This article revisits the foundational elements of ELT, exploring what it is, how it reshaped data strategies, and how it works.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

ProjectPro

JUNE 4, 2015

HDFS in Hadoop architecture provides high throughput access to application data and Hadoop MapReduce provides YARN based parallel processing of large data sets. The basic principle of working behind Apache Hadoop is to break up unstructured data and distribute it into many parts for concurrent data analysis.

Hadoop 52

Hadoop Architecture IT Java 52

Knowledge Hut

DECEMBER 29, 2023

In addition, there are professionals who want to remain current with the most recent capabilities, such as Machine Learning, Deep Learning, and Data Science, in order to further their careers or switch to an entirely other field. However, transitioning to Data Science or beginning a career in data science fields as a novice is not simple.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

DECEMBER 26, 2023

Let us first get a clear understanding of why Data Science is important. What is the need for Data Science? If we look at history, the data that was generated earlier was primarily structured and small in its outlook. This is one of the major reasons behind the popularity of data science.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

ProjectPro

JANUARY 24, 2023

Tired of relentlessly searching for the most effective and powerful data warehousing solutions on the internet? This blog is your comprehensive guide to Google BigQuery, its architecture, and a beginner-friendly tutorial on how to use Google BigQuery for your data warehousing activities. Search no more! Did you know ?

Bytes 52

Bytes Google Cloud Data Warehouse Datasets 52

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

JULY 29, 2022

Depending on how you measure it, the answer will be 11 million newspaper pages or… just one Hadoop cluster and one tech specialist who can move 4 terabytes of textual data to a new location in 24 hours. Developed in 2006 by Doug Cutting and Mike Cafarella to run the web crawler Apache Nutch, it has become a standard for Big Data analytics.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Is Hadoop a data lake or data warehouse? Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

Knowledge Hut

DECEMBER 26, 2023

Big Data is an immense amount of data that is constantly growing exponentially. Due to its vastness and complexity, no traditional data management system can adequately store or process this data. The New York Stock Exchange, which generates one terabyte of new trade data each day, is a classic example of big data.

Big Data 75

Big Data Data Mining Business Intelligence Machine Learning 75

U-Next

OCTOBER 27, 2022

Cloud computing is the term used to describe internet data storage and access. It doesn’t store any data on your computer’s hard drive and allows users to access data from faraway servers. You can easily access as many resources as you require and only pay for those that you utilize. .

AWS 40

AWS Amazon Web Services Cloud Computing Cloud 40

Knowledge Hut

OCTOBER 24, 2023

Business analysts (BAs) oversee bridging the gap between IT and the business by analyzing data to evaluate processes, establish requirements, and offer data-driven recommendations and reports to executives and stakeholders. Knowledge of Programming Business analysts typically work with applicable coding and data.

Business Analyst 98

Business Analyst Business Intelligence SQL Programming Language 98

Knowledge Hut

MAY 4, 2023

Data engineering is all about data storage and organizing and optimizing warehouses plus databases. It helps organizations understand big data and helps in collecting, storing, and analyzing vast amounts of data, using technical skills related to NoSQL, SQL, and hybrid infrastructures.

Data Engineering 52

Data Engineering Data Engineer Engineering Banking 52

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge. Data orchestration.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

Silectis

JANUARY 3, 2021

If you’re new to data engineering or are a practitioner of a related field, such as data science, or business intelligence, we thought it might be helpful to have a handy list of commonly used terms available for you to get up to speed. Big Data Large volumes of structured or unstructured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. That’s exactly what every data-driven organization has been trying to find for years,” someone would come up with a new, better solution.

Architecture 52

Architecture Data Lake Medical Datasets 52

Rockset

OCTOBER 20, 2021

This comes on the heels of our latest product releases around more accessible and affordable real-time analytics with Rollups on Streaming Data and Rockset Views. For high velocity data, most commonly coming from data streams, you can roll it up at write-time. S3 or GCS), NoSQL databases (e.g. PostgreSQL or MySQL).

SQL 52

SQL PostgreSQL MongoDB NoSQL 52

ProjectPro

DECEMBER 10, 2021

Azure Cloud Services are hosted on virtual machines, and they let one have a higher degree of control over the VMs by allowing software installation on the VMs and also making them remotely accessible. A user only pays for the resources he needs from a cloud service provider and accesses them over a secure Internet connection.

BI 52

BI Cloud Computing SQL Database 52