Analytics Vidhya

JUNE 6, 2022

Wouldn’t the process be much easier if the raw data were more organized and clean? Here’s when Data […]. The post What are Schemas in Data Warehouse Modeling? It’s possible, of course, but it can be tiresome and not be as accurate as it should be. appeared first on Analytics Vidhya.

Data Warehouse 309

Data Warehouse Data Science Analytics Analytics 309

Dataconomy

OCTOBER 17, 2023

Want to create a robust data warehouse architecture for your business? The sheer volume of data that companies are now gathering is incredible, and understanding how best to store and use this information to extract top performance can be incredibly overwhelming.

Data Warehouse 103

Data Warehouse Big Data Big Data ETL 103

Analytics Vidhya

APRIL 29, 2022

Introduction Have you ever wondered how big IT giants store and process huge amounts of data? Different organizations make use of different databases like an oracle database storing transactional data, MySQL for storing product data, and many others for different tasks. storing the data […].

Data Warehouse 205

Data Warehouse Database Data Science Analytics 205

Analytics Vidhya

FEBRUARY 21, 2023

This is where data warehousing is a critical component of any business, allowing companies to store and manage vast amounts of data. It provides the necessary foundation for businesses to […] The post Understanding the Basics of Data Warehouse and its Structure appeared first on Analytics Vidhya.

Data Warehouse 234

Data Warehouse Analytics Analytics Azure 234

Analytics Vidhya

FEBRUARY 2, 2023

Now, businesses are looking for different types of data storage to store and manage their data effectively. Organizations can collect millions of data, but if they’re lacking in storing that data, those efforts […] The post A Comprehensive Guide to Data Lake vs. Data Warehouse appeared first on Analytics Vidhya.

Data Warehouse 230

Data Warehouse Data Lakes Analytics Analytics 230

insideBIGDATA

APRIL 22, 2024

In this contributed article, Sida Shen, product marketing manager, CelerData, discusses how data lakehouse architectures promise the combined strengths of data lakes and data warehouses, but one question arises: why do we still find the need to transfer data from these lakehouses to proprietary data warehouses?

Data Warehouse 195

Data Warehouse Data Lakes Big Data Big Data 195

Analytics Vidhya

FEBRUARY 27, 2023

Introduction Data is the new oil in this century. The database is the major element of a data science project. To generate actionable insights, the database must be centralized and organized efficiently. So, we are […] The post How to Normalize Relational Databases With SQL Code?

Database 284

Database SQL Data Science Analytics 284

Dataversity

APRIL 21, 2022

SaaS apps are data-intensive, generating and accessing massive volumes of data in real time. Because of that, most organizations build SaaS apps on data warehouses instead of HTAP databases. For one, since SaaS apps operate on larger volumes of data, data warehouses […].

Data Warehouse 52

Data Warehouse Database 52

Precisely

MARCH 9, 2023

Data warehouse vs. data lake, each has their own unique advantages and disadvantages; it’s helpful to understand their similarities and differences. In this article, we’ll focus on a data lake vs. data warehouse. It lacks many of the important qualities of a traditional database such as ACID compliance.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Apache Hadoop 59

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Data Warehouse 57

Data Warehouse Cloud Data Database Analytics 57

Analytics Vidhya

JUNE 13, 2022

Introduction on ETL Pipeline ETL pipelines are a set of processes used to transfer data from one or more sources to a database, like a data warehouse. Extraction, transformation, and loading are three interdependent procedures used to pull data from one database and place […].

ETL 338

ETL Data Warehouse Database Data Science 338

Analytics Vidhya

JANUARY 6, 2022

INTRODUCTION Hive is one of the most popular data warehouse systems in the industry for data storage, and to store this data Hive uses tables. Tables in the hive are analogous to tables in a relational database management system. By default, it is /user/hive/warehouse directory. For instance, […].

Data Warehouse 314

Data Warehouse Database Analytics Analytics 314

Smart Data Collective

SEPTEMBER 23, 2020

The market for data warehouses is booming. While there is a lot of discussion about the merits of data warehouses, not enough discussion centers around data lakes. We talked about enterprise data warehouses in the past, so let’s contrast them with data lakes. Data Warehouse.

Data Lakes 105

Data Lakes Data Warehouse Big Data Big Data 105

Hacker News

MARCH 28, 2024

A unified SQL query interface and portable runtime to locally materialize, accelerate, and query data tables sourced from any database, data warehouse, or data lake. spiceai/spiceai

SQL 137

SQL Data Lakes Data Warehouse Database 137

Analytics Vidhya

JULY 18, 2022

This article was published as a part of the Data Science Blogathon. Introduction Organizations with a separate transactional database and data warehouse typically have many data engineering activities. For example, they extract, transform and load data from various sources into their data warehouse.

ETL 259

ETL Data Warehouse Data Engineering Data Engineer 259

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction We are all pretty much familiar with the common modern cloud data warehouse model, which essentially provides a platform comprising a data lake (based on a cloud storage account such as Azure Data Lake Storage Gen2) AND a data warehouse compute engine […].

Azure 356

Azure Data Warehouse Data Lakes Analytics 356

Analytics Vidhya

FEBRUARY 19, 2023

Introduction Google’s BigQuery is a powerful cloud-based data warehouse that provides fast, flexible, and cost-effective data storage and analysis capabilities. BigQuery was created to analyse data […] The post Building a Machine Learning Model in BigQuery appeared first on Analytics Vidhya.

Machine Learning 224

Machine Learning Machine Learning Data Warehouse Database 224

Analytics Vidhya

SEPTEMBER 18, 2022

This article was published as a part of the Data Science Blogathon. Introduction Apache SQOOP is a tool designed to aid in the large-scale export and import of data into HDFS from structured data repositories. Relational databases, enterprise data warehouses, and NoSQL systems are all examples of data storage.

Data Warehouse 242

Data Warehouse Database Data Science Analytics 242

Analytics Vidhya

OCTOBER 28, 2021

This article was published as a part of the Data Science Blogathon What is the need for Hive? The official description of Hive is- ‘Apache Hive data warehouse software project built on top of Apache Hadoop for providing data query and analysis.

Apache Hadoop 310

Apache Hadoop Hadoop Data Warehouse SQL 310

Hacker News

NOVEMBER 14, 2023

To further explore this topic, I am surveying real-world serverless, multi-tenant data architectures to understand how different types of systems, such as OLTP databases, real-time OLAP, cloud data warehouses, event streaming systems, and more, implement serverless MT.

Data Warehouse 181

Data Warehouse Cloud Data Database 181

Analytics Vidhya

DECEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. Source: [link] Introduction If you are familiar with databases, or data warehouses, you have probably heard the term “ETL.” As the amount of data at organizations grow, making use of that data in analytics to derive business insights grows as well.

ETL 195

ETL AWS Data Warehouse Database 195

Analytics Vidhya

OCTOBER 4, 2021

This article was published as a part of the Data Science Blogathon Image 1 What is data mining? Data mining is the process of finding interesting patterns and knowledge from large amounts of data. This analysis […].

Data Mining 246

Data Mining Data Mining Data Mining Data Warehouse 246

Analytics Vidhya

SEPTEMBER 27, 2022

Businesses have adopted Snowflake as migration from on-premise enterprise data warehouses (such as Teradata) or a more flexibly scalable and easier-to-manage alternative to […]. The post Data Warehousing with Snowflake and Other Alternatives appeared first on Analytics Vidhya.

Data Warehouse 356

Data Warehouse Data Science Analytics Analytics 356

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Before we address the questions, ‘ What is data version control ?’

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Dataversity

MARCH 1, 2021

Data warehouse (DW) testers with data integration QA skills are in demand. Data warehouse disciplines and architectures are well established and often discussed in the press, books, and conferences. Each business often uses one or more data […]. Each business often uses one or more data […].

Data Warehouse 52

Data Warehouse ETL Data Governance Data Quality 52

Analytics Vidhya

APRIL 1, 2023

Introduction Google Big Query is a secure, accessible, fully-manage, pay-as-you-go, server-less, multi-cloud data warehouse Platform as a Service (PaaS) service provided by Google Cloud Platform that helps to generate useful insights from big data that will help business stakeholders in effective decision-making.

Data Warehouse 266

Data Warehouse SQL Big Data Big Data 266

Flipboard

JULY 11, 2023

ChatGPT will enable users to query the decentralized data warehouse using natural language prompts. Decentralized data startup Space and Time, backed …

Data Warehouse 76

Data Warehouse Database Machine Learning Machine Learning 76

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Analytics Vidhya

FEBRUARY 1, 2023

Introduction Nowadays, organizations are looking for multiple solutions to deal with big data and related challenges.

Data Warehouse 244

Data Warehouse Big Data Big Data Analytics 244

Data Science Blog

SEPTEMBER 19, 2023

In the contemporary age of Big Data, Data Warehouse Systems and Data Science Analytics Infrastructures have become an essential component for organizations to store, analyze, and make data-driven decisions. So why using IaC for Cloud Data Infrastructures?

Data Warehouse 259

Data Warehouse Azure SQL Database 259

Data Science Dojo

JANUARY 12, 2023

When it comes to data, there are two main types: data lakes and data warehouses. What is a data lake? An enormous amount of raw data is stored in its original format in a data lake until it is required for analytics applications. Some NoSQL databases are also utilized as platforms for data lakes.

Data Lakes 222

Data Lakes Data Warehouse Hadoop Machine Learning 222

Analytics Vidhya

JUNE 30, 2022

This article was published as a part of the Data Science Blogathon. Introduction Hive is a popular data warehouse built on top of Hadoop that is used by companies like Walmart, Tiktok, and AT&T. It is an important technology for data engineers to learn and master.

Hadoop 242

Hadoop Data Warehouse Data Engineering Data Engineer 242

Analytics Vidhya

MARCH 14, 2023

This results in the generation of so much data daily. This generated data is stored in the database and will maintain it. SQL is a structured query language used to read and write these databases. Introduction In today’s world, technology has increased tremendously, and many people are using the internet.

SQL 234

SQL Database Analytics Analytics 234

IBM Journey to AI blog

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Data Warehouse 57

Data Warehouse Data Engineering Data Engineer Data Engineering 57

Dataversity

DECEMBER 12, 2022

Here in the early stages of this “stream revolution,” developers are building modern analytics applications that use continuously delivered real-time data. The post Is Your Database Built for Streaming Data? Yet while streams are clearly the […]. appeared first on DATAVERSITY.

Database 52

Database Analytics Analytics Data Warehouse 52

Smart Data Collective

JUNE 15, 2021

However, the value of the data you gather is determined by the quality of the insights you derive from it and how successfully you can incorporate these insights into your company’s infrastructure and future business strategies. This helps companies extract the maximum amount of value from their data sets. 2 – Leverage caching.

Data Warehouse 95

Data Warehouse Database SQL Data Analyst 95

Analytics Vidhya

OCTOBER 25, 2023

Introduction Struggling with expanding a business database due to storage, management, and data accessibility issues? To steer growth, employ effective data management strategies and tools. This article explores data management’s key tool features and lists the top tools for 2023.

Database 208

Database Analytics Analytics Data Warehouse 208