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. What is a data lake?

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

ProjectPro

JUNE 4, 2015

The holistic view of Hadoop architecture gives prominence to Hadoop common, Hadoop YARN, Hadoop Distributed File Systems (HDFS ) and Hadoop MapReduce of the Hadoop Ecosystem. HDFS in Hadoop architecture provides high throughput access to application data and Hadoop MapReduce provides YARN based parallel processing of large data sets.

Hadoop 52

Hadoop Architecture IT Java 52

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? Traditional data warehouse platform architecture. Data lake. Data lake architecture example.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? What is data pipeline architecture? Why is data pipeline architecture important?

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 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

Towards Data Science

FEBRUARY 15, 2023

Concepts, theory, and functionalities of this modern data storage framework Photo by Nick Fewings on Unsplash Introduction I think it’s now perfectly clear to everybody the value data can have. To use a hyped example, models like ChatGPT could only be built on a huge mountain of data, produced and collected over years.

Data Lake 98

Data Lake Data Warehouse Hadoop Architecture 98

Snowflake

JUNE 5, 2024

Cortex AI Cortex Analyst: Enable business users to chat with data and get text-to-answer insights using AI Cortex Analyst, built with Meta’s Llama 3 and Mistral Large models, lets you get the insights you need from your structured data by simply asking questions in natural language.

Coding 112

Coding Building Management Government 112

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 87

Systems Hadoop Metadata Telecommunication 87

AltexSoft

JUNE 7, 2021

The system automatically replicates information to prevent data loss in the case of a node failure. To understand how the entire mechanism works, we need to get familiar with Hadoop structure and key parts. Hadoop architecture, or how the framework works. Data storage options. Hadoop nodes: masters and slaves.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Snowflake

MARCH 30, 2023

Snowflake can also ingest external tables from on-premise s data sources via S3-compliant data storage APIs. Batch/file-based data is modeled into the raw vault table structures as the hub, link, and satellite tables illustrated at the beginning of this post. The friction of data movement is reduced.

Engineering 104

Engineering Raw Data Data Science Machine Learning 104

Knowledge Hut

FEBRUARY 29, 2024

A database is a structured data collection that is stored and accessed electronically. File systems can store small datasets, while computer clusters or cloud storage keeps larger datasets. According to a database model, the organization of data is known as database design.

Data Science 98

Data Science Datasets Machine Learning Database Design 98

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Knowledge Hut

SEPTEMBER 26, 2023

This is particularly valuable in today's data landscape, where information comes in various shapes and sizes. Effective Data Storage: Azure Synapse offers robust data storage solutions that cater to the needs of modern data-driven organizations.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Sync Computing

NOVEMBER 7, 2024

A brief history of data storage The value of data has been apparent for as long as people have been writing things down. Despite these limitations, data warehouses, introduced in the late 1980s based on ideas developed even earlier, remain in widespread use today for certain business intelligence and data analysis applications.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Unstructured Data 52

Monte Carlo

AUGUST 25, 2023

Data teams need to balance the need for robust, powerful data platforms with increasing scrutiny on costs. That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. Let’s dive in.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

ProjectPro

AUGUST 11, 2021

Table of Contents Data Lake vs Data Warehouse - The Differences Data Lake vs Data Warehouse - The Introduction What is a Data warehouse? Data Warehouse Architecture What is a Data lake? Data is generally not loaded into a data warehouse unless a use case has been defined for the data.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 52

RandomTrees

SEPTEMBER 6, 2020

Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS). Built on new SQL database engine, it provides a unique architecture designed for the cloud.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

ProjectPro

SEPTEMBER 9, 2021

Hive comparison elaborates on the two tools’ architecture, features, limitations, and key differences. The following is the architecture of Hive. Apache Hive Architecture Apache Hive has a simple architecture with a Hive interface, and it uses HDFS for data storage.

Hadoop 52

Hadoop Big Data Tools Java Big Data 52

Knowledge Hut

MARCH 27, 2024

Scales efficiently for specific operations within algorithms but may face challenges with large-scale data storage. Database vs Data Structure If you are thinking about how to differentiate database and data structure, let me explain the difference between the two in detail on the parameters mentioned above in the table.

Database 52

Database Relational Database Algorithm Data Storage 52

AltexSoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

IT 59

IT Data Warehouse Data Governance Data Lake 59

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). The framework itself is extensible to run custom jobs.

Big Data 78

Big Data Data Management Management Metadata 78

AltexSoft

MAY 14, 2021

A growing number of companies now use this data to uncover meaningful insights and improve their decision-making, but they can’t store and process it by the means of traditional data storage and processing units. Key Big Data characteristics. And most of this data has to be handled in real-time or near real-time.

Big Data 78

Big Data Data Analytics IT NoSQL 78

Knowledge Hut

MARCH 15, 2024

RDBMS vs NoSQL: Benefits RDBMS: Data Integrity: Enforces relational constraints, ensuring consistency. Structured Data: Ideal for complex relationships between entities. NoSQL: Scalability: Easily scales horizontally to handle large volumes of data. Denormalization: Emphasizes performance by storing redundant data.

NoSQL 52

NoSQL Database-centric Relational Database PostgreSQL 52

Knowledge Hut

DECEMBER 26, 2023

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications.

Data Science 97

Data Science BI Machine Learning Business Intelligence 97

Knowledge Hut

MAY 2, 2024

To store and process even only a fraction of this amount of data, we need Big Data frameworks as traditional Databases would not be able to store so much data nor traditional processing systems would be able to process this data quickly. But, in the majority of cases, Hadoop is the best fit as Spark’s data storage layer.

Hadoop 96

Hadoop Scala Datasets Java 96

Grouparoo

DECEMBER 26, 2021

For data storage, the database is one of the fundamental building blocks. What are the Different Types of Database Architectures? NoSQL databases are horizontally scalable; adding additional processing and storage facilities to manage new instances of the database will increase the size of the database.

Database 52

Database NoSQL Relational Database Data Storage 52

Knowledge Hut

APRIL 25, 2023

It provides a flexible data model that can handle different types of data, including unstructured and semi-structured data. Key features: Flexible data modeling High scalability Support for real-time analytics 4. Key features: Instant elasticity Support for semi-structured data Built-in data security 5.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

AltexSoft

AUGUST 4, 2021

A data warehouse (DW) is a data repository that allows for storing and managing all the historical enterprise data, coming from disparate internal and external sources like CRMs, ERPs, flat files, etc. Initially, DWs dealt with structured data presented in tabular forms. Data mart constructing.

Data Lake 64

Data Lake Data Warehouse ETL Tools Database 64

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 infrastructure, data warehousing, data mining, data modeling, etc.,

Data Engineering 52

Data Engineering Data Engineer Engineering Data Storage 52

Cloudera

OCTOBER 3, 2018

Google built an innovative scale-out platform for data storage and analysis in the late 1990s and early 2000s, and published research papers about their work. Today, the market includes a growing collection of companies who recognize what we both knew early — big data is a big deal.

Hadoop 75

Hadoop Cloud Data Storage Machine Learning 75

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

Data warehouses are typically built using traditional relational database systems, employing techniques like Extract, Transform, Load (ETL) to integrate and organize data. Data warehousing offers several advantages. By structuring data in a predefined schema, data warehouses ensure data consistency and accuracy.

Data Warehouse 52

Data Warehouse Big Data Unstructured Data Hadoop 52

Knowledge Hut

JANUARY 18, 2024

4 Purpose Utilize the derived findings and insights to make informed decisions The purpose of AI is to provide software capable enough to reason on the input provided and explain the output 5 Types of Data Different types of data can be used as input for the Data Science lifecycle.

Data Science 98

Data Science Deep Learning Business Analyst Data Mining 98

Edureka

FEBRUARY 9, 2023

An Azure Data Engineer is a highly qualified expert who is in charge of integrating, transforming, and merging data from various structured and unstructured sources into a structure that can be used to build analytics solutions. Data engineers must be well-versed in programming languages such as Python, Java, and Scala.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 52

Netflix Tech

DECEMBER 14, 2018

In the previous blog posts in this series, we introduced the N etflix M edia D ata B ase ( NMDB ) and its salient “Media Document” data model. In this post we will provide details of the NMDB system architecture beginning with the system requirements?—?these key value stores generally allow storing any data under a key).

Media 99

Media Database Metadata Data Schemas 99

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

JULY 18, 2023

These seemingly unrelated terms unite within the sphere of big data, representing a processing engine that is both enduring and powerfully effective — Apache Spark. Spark SQL brings native support for SQL to Spark and streamlines the process of querying semistructured and structured data. Apache Spark architecture in a nutshell.

Big Data 52

Big Data Data Process Process Hadoop 52