insideBIGDATA

JUNE 23, 2023

CEO and co-founder of Simon Data, believes that when companies try to pull together all the data streams in a warehouse, they can run into several challenges that make it hard to get a comprehensive picture and create effective personalization. In this contributed article, Jason Davis, Ph.D.

Data Warehouse 397

Data Warehouse Cloud Data Big Data Big Data 397

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 267

Data Warehouse Database Data Science Analytics 267

Analytics Vidhya

MARCH 27, 2024

Introduction This article will introduce the concept of data modeling, a crucial process that outlines how data is stored, organized, and accessed within a database or data system. It involves converting real-world business needs into a logical and structured format that can be realized in a database or data warehouse.

Data Modeling 306

Data Modeling Data Models Database Data Warehouse 306

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 290

Data Warehouse Analytics Analytics Azure 290

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 289

Data Warehouse Data Lakes Analytics Analytics 289

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

insideBIGDATA

JUNE 30, 2023

In this contributed article, Chris Tweten, Marketing Representative of AirOps, discusses how data warehouse best practices give digital businesses a solid foundation for building a streamlined data management system. Here’s what you need to know.

Data Warehouse 243

Data Warehouse Cloud Data Big Data Big Data 243

insideBIGDATA

SEPTEMBER 18, 2024

Firebolt announced the next-generation Cloud Data Warehouse (CDW) that delivers low latency analytics with drastic efficiency gains. Built across five years of relentless development, it reflects continuous feedback from users and real-world use cases.

Data Warehouse 221

Data Warehouse Cloud Data Analytics Analytics 221

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 221

Data Lakes Data Warehouse Hadoop Machine Learning 221

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 364

Data Warehouse Database Analytics Analytics 364

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 319

Database SQL Data Science Analytics 319

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 361

ETL Data Warehouse Database Data Science 361

Analytics Vidhya

JULY 1, 2024

It serves as the primary means for communicating with relational databases, where most organizations store crucial data. SQL plays a significant role including analyzing complex data, creating data pipelines, and efficiently managing data warehouses.

SQL 316

SQL Data Warehouse Data Pipeline Database 316

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 398

Azure Data Warehouse Data Lakes Analytics 398

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 349

Apache Hadoop Data Warehouse Hadoop SQL 349

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 291

ETL Data Warehouse Data Engineer Data Engineering 291

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 324

Data Mining Data Mining Data Mining Data Warehouse 324

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 397

Data Warehouse Data Science Analytics Analytics 397

Data Science Blog

MAY 20, 2024

Enter AnalyticsCreator AnalyticsCreator, a powerful tool for data management, brings a new level of efficiency and reliability to the CI/CD process. It offers full BI-Stack Automation, from source to data warehouse through to frontend. It supports a holistic data model, allowing for rapid prototyping of various models.

Data Pipeline 262

Data Pipeline Data Warehouse Azure Data Lakes 262

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 271

Data Warehouse Data Science Database Analytics 271

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 270

Machine Learning Machine Learning Data Warehouse Database 270

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

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 110

Data Lakes Data Warehouse Big Data Big Data 110

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 218

ETL AWS Data Warehouse Data Science 218

Analytics Vidhya

FEBRUARY 1, 2023

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

Data Warehouse 305

Data Warehouse Big Data Big Data Analytics 305

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 306

Data Warehouse SQL Big Data Big Data 306

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 221

Data Warehouse Data Lakes Big Data Big Data 221

Data Science Dojo

APRIL 25, 2023

SQL (Structured Query Language) is an important tool for data scientists. It is a programming language used to manipulate data stored in relational databases. Mastering SQL concepts allows a data scientist to quickly analyze large amounts of data and make decisions based on their findings.

Data Scientist 370

Data Scientist SQL Machine Learning Machine Learning 370

Dataconomy

MAY 27, 2024

The main solutions on the market are decentralized file storage networks (DSFN) like Filecoin and Arweave, and decentralized data warehouses like Space and Time (SxT). Built to seamlessly integrate with existing enterprise systems, the data warehouse lets businesses tap into blockchain data while publishing query results back on-chain.

Data Warehouse 213

Data Warehouse Database SQL Analytics 213

Flipboard

NOVEMBER 27, 2024

While customers can perform some basic analysis within their operational or transactional databases, many still need to build custom data pipelines that use batch or streaming jobs to extract, transform, and load (ETL) data into their data warehouse for more comprehensive analysis. or a later version) database.

ETL 138

ETL Data Warehouse Analytics Analytics 138

Dataconomy

APRIL 27, 2023

What is an online transaction processing database (OLTP)? OLTP is the backbone of modern data processing, a critical component in managing large volumes of transactions quickly and efficiently. This approach allows businesses to efficiently manage large amounts of data and leverage it to their advantage in a highly competitive market.

Database 159

Database Data Scientist Data Mining Data Mining 159

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.

Data Warehouse 271

Data Warehouse Hadoop Data Engineer Data Engineering 271

AWS Machine Learning Blog

OCTOBER 24, 2024

Built into Data Wrangler, is the Chat for data prep option, which allows you to use natural language to explore, visualize, and transform your data in a conversational interface. Amazon QuickSight powers data-driven organizations with unified (BI) at hyperscale. A provisioned or serverless Amazon Redshift data warehouse.

Data Warehouse 122

Data Warehouse Machine Learning Machine Learning Cloud Data 122

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 138

SQL Data Lakes Data Warehouse Database 138

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

Pickl AI

DECEMBER 15, 2024

Summary : This guide provides an in-depth look at the top data warehouse interview questions and answers essential for candidates in 2025. Covering key concepts, techniques, and best practices, it equips you with the knowledge needed to excel in interviews and demonstrates your expertise in data warehousing.

Data Warehouse 52

Data Warehouse ETL Database Data Quality 52

Smart Data Collective

FEBRUARY 20, 2022

Since databases store companies’ valuable digital assets and corporate secrets, they are on the receiving end of quite a few cyber-attack vectors these days. How can database activity monitoring (DAM) tools help avoid these threats? What are the ties between DAM and data loss prevention (DLP) systems? How do DAM solutions work?

Database 127

Database Machine Learning Machine Learning Data Warehouse 127