Analytics Vidhya

APRIL 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Have you ever wondered how big IT giants store and process huge amounts of data? storing the data […]. 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.

Data Modeling 306

Data Modeling Data Models Database Data Warehouse 306

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 244

Data Warehouse Cloud Data Big Data Big Data 244

Analytics Vidhya

JUNE 13, 2022

This article was published as a part of the Data Science Blogathon. 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.

ETL 361

ETL Data Warehouse Database Data Science 361

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 222

Data Warehouse Cloud Data Analytics Analytics 222

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. The post How a Delta Lake is Process with Azure Synapse Analytics appeared first on Analytics Vidhya.

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 Engineering Data Engineering 291

Analytics Vidhya

SEPTEMBER 27, 2022

This article was published as a part of the Data Science Blogathon. 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 […].

Data Warehouse 397

Data Warehouse Data Science Analytics Analytics 397

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 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

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 222

Data Warehouse Data Lakes Big Data Big Data 222

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 216

ETL AWS Data Warehouse Data Science 216

Dataversity

FEBRUARY 5, 2025

In the first part of this series, we explored how harmonizing relational database management systems (RDBMS) with data warehouses (DWH) can drive scalability, efficiency, and advanced analytics.

Data Warehouse 52

Data Warehouse Database Analytics Analytics 52

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 Engineering Data Engineering 271

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

JULY 1, 2022

This article was published as a part of the Data Science Blogathon. Introduction In the field of Data Science main types of online processing systems are Online Transaction Processing (OLTP) and Online Analytical Processing (OLAP), which are used in most companies for transaction-oriented applications and analytical work.

Data Science 270

Data Science Database Analytics Analytics 270

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 130

Database Machine Learning Machine Learning Data Warehouse 130

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 220

Database Analytics Analytics Data Warehouse 220

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

Analytics Vidhya

JULY 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Processing large amounts of raw data from various sources requires appropriate tools and solutions for effective data integration. Building an ETL pipeline using Apache […].

ETL 383

ETL Data Science Analytics Analytics 383

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. They are typically exploring data in the same ways, repeated over the course of time.

Data Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Analytics Vidhya

JULY 20, 2022

This article was published as a part of the Data Science Blogathon. Introduction Data acclimates to countless shapes and sizes to complete its journey from a source to a destination. The post Developing an End-to-End Automated Data Pipeline appeared first on Analytics Vidhya.

Data Pipeline 361

Data Pipeline ETL Data Science Analytics 361

Analytics Vidhya

FEBRUARY 28, 2023

This data is used by an organization to find valuable insights which help in improving an organization’s growth and strategies and give them an upper hand over its competitors. This article explains to you the idea […] The post Understanding Dimensional Modeling appeared first on Analytics Vidhya.

Analytics 326

Analytics Analytics Data Warehouse Data Engineering 326

Analytics Vidhya

NOVEMBER 19, 2022

This article was published as a part of the Data Science Blogathon. Introduction The rate of data expansion in this decade is rapid. The requirement to process and store these data has also become problematic.

Cloud Data 329

Cloud Data Data Science Analytics Analytics 329

Analytics Vidhya

JULY 25, 2022

This article was published as a part of the Data Science Blogathon. Introduction These days companies seem to seek ways to integrate data from multiple sources to earn a competitive advantage over other businesses.

Data Pipeline 327

Data Pipeline Data Science Analytics Analytics 327

ODSC - Open Data Science

SEPTEMBER 27, 2023

As data lakes gain prominence as a preferred solution for storing and processing enormous datasets, the need for effective data version control mechanisms becomes increasingly evident. Understanding Data Lakes A data lake is a centralized repository that stores structured, semi-structured, and unstructured data in its raw format.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Smart Data Collective

OCTOBER 27, 2021

Interactive analytics applications make it easy to get and build reports from large unstructured data sets fast and at scale. In this article, we’re going to look at the top 5. Firebolt makes engineering a sub-second analytics experience possible by delivering production-grade data applications & analytics. Google BigQuery.

Analytics 130

Analytics Analytics Data Warehouse Business Intelligence 130

Analytics Vidhya

AUGUST 16, 2022

This article was published as a part of the Data Science Blogathon. Introduction The Data science pipeline is the procedure and equipment used to compile raw data from many sources, evaluate it, and display the findings in a clear and concise manner.

Data Science 291

Data Science Analytics Analytics Data Warehouse 291

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

JUNE 28, 2022

This article was published as a part of the Data Science Blogathon. “Preponderance data opens doorways to complex and Avant analytics.” ” Introduction to SQL Queries Data is the premium product of the 21st century.

SQL 270

SQL Data Science Analytics Analytics 270

Dataversity

DECEMBER 15, 2021

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization. For example, most data warehouses […].

Data Warehouse 98

Data Warehouse Data Lakes Database Business Intelligence 98

Dataconomy

MARCH 4, 2025

Data mining is a fascinating field that blends statistical techniques, machine learning, and database systems to reveal insights hidden within vast amounts of data. Businesses across various sectors are leveraging data mining to gain a competitive edge, improve decision-making, and optimize operations.

Data Mining 91

Data Mining Data Mining Data Mining Decision Trees 91

Dataversity

MAY 6, 2022

An underlying architectural pattern is the leveraging of an open data lakehouse. That is no surprise – open data lakehouses can easily handle digital-era data types that traditional data warehouses were not designed for. Data warehouses are great at both analyzing and storing […].

Data Warehouse 98

Data Warehouse Data Lakes Database 98

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. Let’s break down each step: 1.

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ETL Data Quality Data Warehouse Analytics 105

Dataversity

NOVEMBER 6, 2024

As businesses grow, so does the complexity of managing and analyzing data. Traditionally, relational database management systems (RDBMS) have been the backbone of data storage, offering robust and reliable transactional capabilities.

Database 59

Database Data Warehouse 59

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 58

Data Warehouse Data Engineering Data Engineer Data Engineering 58