Monte Carlo

JANUARY 5, 2024

You know what they always say: data lakehouse architecture is like an onion. …ok, Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. But they should!

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 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.

MongoDB 40

MongoDB Architecture NoSQL MySQL 40

AltexSoft

NOVEMBER 10, 2021

The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. What is a data lakehouse? Data warehouse. Traditional data warehouse platform architecture. Lakehouse architecture.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

AUGUST 29, 2023

Data lakes emerged as expansive reservoirs where raw data in its most natural state could commingle freely, offering unprecedented flexibility and scalability. This article explains what a data lake is, its architecture, and diverse use cases. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. As data is expanding exponentially, organizations struggle to harness digital information's power for different business use cases. What is a Big Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

AltexSoft

JUNE 7, 2021

The system automatically replicates information to prevent data loss in the case of a node failure. Hadoop architecture, or how the framework works. MapReduce performs batch processing only and doesn’t fit time-sensitive data or real-time analytics jobs. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

AltexSoft

AUGUST 22, 2022

In this post, we’ll attempt to explain the idea behind a data fabric, its architectural building blocks, the benefits it brings, and ways to approach its implementation. What is data fabric? to provide a unified view of all enterprise data. Data fabric architecture example. Data fabric vs data mesh.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

U-Next

SEPTEMBER 7, 2022

Structuring data refers to converting unstructured data into tables and defining data types and relationships based on a schema. The data lakes store data from a wide variety of sources, including IoT devices, real-time social media streams, user data, and web application transactions.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Amazon Web Services 52

ProjectPro

AUGUST 24, 2016

Facebook Messenger uses HBase architecture and many other companies like Flurry, Adobe Explorys use HBase in production. You might have come across several resources that explain HBase architecture and guide you through HBase installation process. HBase provides real-time read or write access to data in HDFS.

Architecture 40

Architecture IT Hadoop NoSQL 40

Striim

SEPTEMBER 11, 2024

Data pipelines are the backbone of your business’s data architecture. Implementing a robust and scalable pipeline ensures you can effectively manage, analyze, and organize your growing data. Benjamin Kennedy, Cloud Solutions Architect at Striim, emphasizes the outcome-driven nature of data pipelines.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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

MARCH 19, 2015

RDBMS is not always the best solution for all situations as it cannot meet the increasing growth of unstructured data. As data processing requirements grow exponentially, NoSQL is a dynamic and cloud friendly approach to dynamically process unstructured data with ease.IT

NoSQL 49

NoSQL Big Data SQL Database-centric 49

AltexSoft

FEBRUARY 11, 2023

This specialist works closely with people on both business and IT sides of a company to understand the current needs of the stakeholders and help them unlock the full potential of data. To get a better understanding of a data architect’s role, let’s clear up what data architecture is.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Rockset

JUNE 7, 2022

Editor Databases are a key architectural component of many applications and services. Traditionally, organizations have chosen relational databases like SQL Server, Oracle , MySQL and Postgres. Relational databases use tables and structured languages to store data.

MongoDB 52

MongoDB NoSQL Relational Database Non-relational Database 52

Knowledge Hut

APRIL 23, 2024

It is designed to support business intelligence (BI) and reporting activities, providing a consolidated and consistent view of enterprise data. Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

ProjectPro

FEBRUARY 8, 2023

Let us dive deeper into this data integration solution by AWS and understand how and why big data professionals leverage it in their data engineering projects. The ETL code for your data is automatically generated by AWS Glue when you specify your ETL process in the drag-and-drop job editor. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98

AltexSoft

MAY 14, 2021

And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. This data isn’t just about structured data that resides within relational databases as rows and columns. Hadoop architecture layers. Apache Hadoop. Source: phoenixNAP.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

Knowledge Hut

APRIL 23, 2024

Below are some of the differences between Traditional Databases vs big data: Parameters Big Data Traditional Data Flexibility Big data is more flexible and can include both structured and unstructured data. Traditional Data is based on a static schema that can only work well with structured data.

Big Data 52

Big Data Relational Database Data Structured Data 52

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

Knowledge Hut

NOVEMBER 2, 2023

Building a Serverless API with AWS Lambda Difficulty Level: Intermediate Explore serverless architectures on AWS with simple projects such as creating an API with AWS Lambda. Professionals deploy databases, manage credentials and access, and integrate with other AWS services or applications.

AWS 52

AWS Coding Cloud Project 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. They can be accumulated in NoSQL databases like MongoDB or Cassandra.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

DECEMBER 26, 2023

Data Engineers are skilled professionals who lay the foundation of databases and architecture. Using database tools, they create a robust architecture and later implement the process to develop the database from zero. As a Data engineer, you need to be quite proficient in SQL and NoSQL.

Data Engineering 98

Data Engineering Data Engineer Engineering Hadoop 98

Workfall

MARCH 21, 2023

It is highly available, scalable, and distributed, and it supports: SQL querying from client devices GraphQL ACID transactions WebSocket connections Both structured and unstructured data Graph querying Full-text indexing Geospatial querying Row permission-based access SurrealQL is an out-of-the-box SQL-style query language included with SurrealDB.

PostgreSQL 68

PostgreSQL NoSQL Database Unstructured Data 68

Knowledge Hut

JULY 26, 2023

It also has strong querying capabilities, including a large number of operators and indexes that allow for quick data retrieval and analysis. Database Software- Other NoSQL: NoSQL databases cover a variety of database software that differs from typical relational databases. Columnar Database (e.g.-

Database 52

Database NoSQL MongoDB Telecommunication 52

Silectis

JANUARY 3, 2021

Big Data Large volumes of structured or unstructured data. Big Data Processing In order to extract value or insights out of big data, one must first process it using big data processing software or frameworks, such as Hadoop. Big Query Google’s cloud data warehouse.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

JUNE 23, 2023

Go for the best courses for Data Engineering and polish your big data engineer skills to take up the following responsibilities: You should have a systematic approach to creating and working on various data architectures necessary for storing, processing, and analyzing large amounts of data. What is COSHH?

Data Engineering 52

Data Engineering Data Engineer Engineering NoSQL 52

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 Relational Database AWS 52

AltexSoft

NOVEMBER 23, 2021

To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization. This post is a perfect place to learn about this approach, its architecture components, differences, benefits, tools, and more. What is data virtualization?

Process 69

Process Data Lake Metadata Data Warehouse 69

Knowledge Hut

MARCH 19, 2024

AWS EC2 use cases consist of: With options for load balancing and auto-scaling, create a fault-tolerant architecture. It is the perfect fit for complex daily database requirements that are OLTP/transactional. The AWS architecture case study includes HIPAA, SOC2, and HITRUST certification requirements.

AWS 52

AWS Amazon Web Services Hospitality Cloud Computing 52

Knowledge Hut

SEPTEMBER 22, 2023

Knowledge of cloud principles and an awareness of the fundamental elements of Azure's architecture are among the abilities assessed in the certification examinations. Data Engineers On-site and cloud data platform technologies are configured and provisioned by data engineers.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

SEPTEMBER 28, 2023

My mission is to serve as the bridge between the intricacies of technology and the aspirations of our clients, harnessing the skills imperative for AWS Solution Architecture. Here are some AWS solution architect key skills and design principles for AWS architecture a. The basis for scalable and resilient applications is networking.

AWS 52

AWS Cloud Computing Architecture Utilities 52

Knowledge Hut

SEPTEMBER 26, 2023

Because we have to often collaborate with cross-functional teams and are in charge of translating the requirements of data scientists and analysts into technological solutions, Azure Data Engineers need excellent problem-solving and communication skills in addition to technical expertise. is the responsibility of data engineers.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Knowledge Hut

JULY 24, 2023

According to recent studies, the global database market will grow from USD 63.4 SQL is a powerful tool for managing and manipulating relational databases, and it continues to be widely used in the industry today. One of its most significant benefits is its ability to quickly process a vast amount of data.

Database 52

Database SQL Process NoSQL 52

Knowledge Hut

DECEMBER 29, 2023

A Data Engineer's primary responsibility is the construction and upkeep of a data warehouse. In this role, they would help the Analytics team become ready to leverage both structured and unstructured data in their model creation processes. They construct pipelines to collect and transform data from many sources.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

ProjectPro

JANUARY 19, 2022

An Azure Data Engineer is a highly qualified expert responsible for integrating, transforming, and merging data from various structured and unstructured sources into a structure used to construct analytics solutions. Data engineering is a new and ever-evolving field that can withstand the test of time and computing developments.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52