Analytics Vidhya

SEPTEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction The concept of data warehousing dates to the 1980s. DHW, short for Data Warehouse, was presented first by great IBM researchers Barry Devlin and Paul […].

Data Warehouse 207

Data Warehouse Analytics Data Science Publishing 207

Analytics Vidhya

OCTOBER 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Snowflake has long been a Cloud Data Warehouse. The post Data Exchange with Modern Data Warehouse – Snowflake appeared first on Analytics Vidhya.

Data Warehouse 229

Data Warehouse Analytics Data Science Publishing 229

Analytics Vidhya

SEPTEMBER 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction to Data Warehouse SQL Data Warehouse is also a cloud-based data warehouse that uses Massively Parallel Processing (MPP) to run complex queries across petabytes of data rapidly.

Data Warehouse 176

Data Warehouse Analytics Big Data Data Science 176

Analytics Vidhya

JUNE 2, 2022

This article was published as a part of the Data Science Blogathon. Introduction The following is an in-depth article explaining what data warehousing is as well as its types, characteristics, benefits, and disadvantages. What is a data warehouse?

Data Warehouse 227

Data Warehouse Data Science Publishing IT 227

Advertisement

A next-gen cloud data lake architecture has emerged that brings together the best attributes of the data warehouse and the data lake. This new open data architecture is built to maximize data access with minimal data movement and no data copies.

Data Lake

Analytics Vidhya

SEPTEMBER 13, 2022

This article was published as a part of the Data Science Blogathon. Introduction The purpose of a data warehouse is to combine multiple sources to generate different insights that help companies make better decisions and forecasting.

Data Warehouse 228

Data Warehouse Forecasting Analytics Big Data 228

Analytics Vidhya

OCTOBER 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Like many marketers, I’m sure your marketing data comes from multiple platforms, and you must juggle a mix of classified data to analyze and understand your customer journey.

Data Warehouse 253

Data Warehouse Marketing Data Science Publishing 253

Analytics Vidhya

OCTOBER 15, 2022

This article was published as a part of the Data Science Blogathon. Introduction Data from different sources are brought to a single location and then converted into a format that the data warehouse can process and store.

Data Warehouse 248

Data Warehouse Analytics IT Sales 248

Analytics Vidhya

JUNE 6, 2022

This article was published as a part of the Data Science Blogathon. Introduction Do you think you can derive insights from raw data? Wouldn’t the process be much easier if the raw data were more organized and clean? Here’s when Data […].

Data Warehouse 225

Data Warehouse Modeling Analytics Data Science 225

Analytics Vidhya

JANUARY 7, 2022

Introduction All data mining repositories have a similar purpose: to onboard data for reporting intents, analysis purposes, and delivering insights. By their definition, the types of data it stores and how it can be accessible to users differ.

Data Lake 258

Data Lake Data Warehouse Data mining Analytics 258

Analytics Vidhya

OCTOBER 28, 2022

This article was published as a part of the Data Science Blogathon. Introduction Data is defined as information that has been organized in a meaningful way. Data collection is critical for businesses to make informed decisions, understand customers’ […].

Data Lake 233

Data Lake Data Warehouse Analytics Data Collection 233

Advertisement

Enterprises poured $73 billion into data management software in 2020 – but are seeing very little return on their data investments. 22% of data leaders surveyed have fully realized ROI in the past two years, with 56% having no consistent way of measuring it.

Measurement

Analytics Vidhya

JUNE 11, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Snowflake Architecture This article helps to focus on an in-depth understanding of Snowflake architecture, how it stores and manages data, as well as its conceptual fragmentation concepts.

Data Warehouse 202

Data Warehouse Analytics Data Science Publishing 202

Analytics Vidhya

MAY 3, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Data Warehouses During one of the technical webinars, it was highlighted where the transactional database was rendered no-operational bringing day to day operations to a standstill.

Data Warehouse 203

Data Warehouse Analytics Data Science Publishing 203

Analytics Vidhya

MARCH 25, 2022

This article was published as a part of the Data Science Blogathon. A data warehouse (DW) is a key component of business intelligence that brings together data from a variety of sources into a single data repository for advanced analytics and decision support.

Data Warehouse 228

Data Warehouse Analytics Business Intelligence Data Science 228

Analytics Vidhya

JULY 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction Hello, data-enthusiast! In this article let’s discuss “Data Modelling” right from the traditional and classical ways and aligning to today’s digital way, especially for analytics and advanced analytics.

Data Warehouse 184

Data Warehouse Modeling Analytics Publishing 184

Analytics Vidhya

AUGUST 5, 2022

This article was published as a part of the Data Science Blogathon. The post Building Data Warehouse Using Google Big Query appeared first on Analytics Vidhya. Big data Cloud Computing Data Warehouse Intermediate big query blogathon Google Cloud

Data Warehouse 193

Data Warehouse Analytics Data-driven Data Science 193

Advertisement

Data architectures have evolved dramatically. It is time to reconsider the fundamental ways that information is accumulated, managed, and then provisioned to the different downstream data consumers.

Data Architecture

Analytics Vidhya

APRIL 25, 2022

This article was published as a part of the Data Science Blogathon. Introduction Amazon’s Redshift Database is a cloud-based large data warehousing solution. The post AWS Redshift: Cloud Data Warehouse Service appeared first on Analytics Vidhya.

Data Warehouse 193

Data Warehouse Analytics Data Science Publishing 193

DataFloq

OCTOBER 8, 2021

We experience the great impact of data both on our lives and business. But those great amounts of data must be stored and analyzed in an effective way. It is a crucial part of an organization as the data stored is a valuable asset. Big Data

Data Lake 255

Data Lake Data Warehouse Unstructured Data Data-driven 255

Analytics Vidhya

JULY 6, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction A Data Warehouse is Built by combining data from multiple. The post A Brief Introduction to the Concept of Data Warehouse appeared first on Analytics Vidhya.

Data Warehouse 222

Data Warehouse Analytics Data Science Publishing 222

David Menninger's Analyst Perspectives

MAY 7, 2020

In this analyst perspective, Dave Menninger takes a look at data lakes. He explains the term “data lake,” describes common use cases and shares his views on some of the latest market trends.

Data Lake 232

Data Lake Data Warehouse Risk Marketing 232

Advertisement

This paper will discuss why organizations frequently end up with multiple data copies and how a secure "no-copy" data strategy enabled by the Dremio data lake service can help reduce complexity, boost efficiency, and dramatically reduce costs.

Data Lake

Analytics Vidhya

JUNE 20, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Data warehouse generalizes and mingles data in multidimensional space. The post How to Build a Data Warehouse Using PostgreSQL in Python?

Data Warehouse 257

Data Warehouse Analytics Data Science Publishing 257

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 […].

Data Warehouse 164

Data Warehouse Analytics Data Science Publishing 164

Analytics Vidhya

OCTOBER 21, 2020

Overview Understand the meaning of data lake and data warehouse We will see what are the key differences between Data Warehouse and Data Lake. The post What are the differences between Data Lake and Data Warehouse?

Data Lake 232

Data Lake Data Warehouse Analytics 232

Data Virtualization

OCTOBER 18, 2022

The post The Data Warehouse is Dead, Long Live the Data Warehouse, Part I appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Warehouse 83

Data Warehouse ROI Internet of Things Data Integration 83

Advertisement

In this paper, we explore the top considerations for building a cloud data lake including architectural principles, when to use cloud data lake engines and how to empower non-technical users.

Data Lake

DataFloq

MARCH 10, 2022

Struggling to harness data sprawl, CIOs across industries are facing tough challenges. One of them is where to store all of their enterprise’s data to deliver robust data analytics. There have traditionally been two storage solutions for data: data warehouses and data lakes.

Data Lake 243

Data Lake Data Warehouse Metadata OLAP 243

KDnuggets

MAY 17, 2022

Is the data warehouse broken? Is the "immutable data warehouse" the right path for your data team? KDnuggets Originals Data ScienceLearn more here.

Data Warehouse 80

Data Warehouse Data Science 80

KDnuggets

SEPTEMBER 14, 2022

So where can you store, harness and collect findings in your data - in one place? Data Warehouses. KDnuggets Originals Data ScienceWhat is the right tool for this?

Data Warehouse 58

Data Warehouse Data Science 58

Alation

JULY 28, 2022

There was a time when most CIOs would never consider putting their crown jewels — AKA customer data and associated analytics — into the cloud. But today, there is a magic quadrant for cloud databases and warehouses comprising more than 20 vendors. Data quality /wrangling.

Data Warehouse 56

Data Warehouse Snapshot Risk Data Governance 56

Smart Data Collective

AUGUST 28, 2021

Data lakes and data warehouses are probably the two most widely used structures for storing data. Data Warehouses and Data Lakes in a Nutshell. The stored data is unprocessed, and the structure is usually applied when it is retrieved.

Data Lake 109

Data Lake Data Warehouse Data Collection Structured Data 109

Analytics Vidhya

MAY 30, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Different components in the Hadoop Framework Introduction Hadoop is. The post HIVE – A DATA WAREHOUSE IN HADOOP FRAMEWORK appeared first on Analytics Vidhya.

Data Warehouse 185

Data Warehouse Analytics Data Science Publishing 185

The Data Administration Newsletter

SEPTEMBER 14, 2021

Data lake is a newer IT term created for a new category of data store. But just what is a data lake? According to IBM, “a data lake is a storage repository that holds an enormous amount of raw or refined data in native format until it is accessed.”

Data Lake 76

Data Lake Data Warehouse IT Data Strategy 76

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 Lake 87

Data Lake Data Warehouse Data Collection Unstructured Data 87

Data Virtualization

NOVEMBER 24, 2022

Reading Time: 4 minutes My previous post explained that, in my mind, the data lakehouse differs hardly at all from the traditional data warehouse architectural design pattern (ADP).

Data Warehouse 52

Data Warehouse Data Integration Technology Management 52

KDnuggets

DECEMBER 1, 2021

ELT helps to streamline the process of modern data warehousing and managing a business’ data. In this post, we’ll discuss some of the best ELT tools to help you clean and transfer important data to your data warehouse.

Data Warehouse 70

Data Warehouse Management Data Science 70

Octopai

DECEMBER 26, 2022

Migrating a data fulfillment center (i.e. warehouse). Your data warehouse is not too different from an Amazon fulfillment center. Your old data warehouse has become deprecated. It’s time to commence a data warehouse migration project.

Data Warehouse 79

Data Warehouse Testing IT Reporting 79

Cloudera

APRIL 9, 2021

Enterprise data warehouse platform owners face a number of common challenges. In this article, we look at seven challenges, explore the impacts to platform and business owners and highlight how a modern data warehouse can address them. Data Types & Access Patterns.

Data Warehouse 56

Data Warehouse Statistics Interactive Visualization 56

Corinium

APRIL 29, 2019

Are you extracting maximum insights from your data? Data is the same. Conventional data warehouses can’t handle the volume, complexity, and variety of today’s data, and they can’t empower all your teams to access and analyze that data in real time. Focusing on data-driven decision-making instead of on administration and maintenance. You know crude oil is more valuable when it’s processed.

Data Warehouse 150

Data Warehouse Data Quality Data-driven IT 150

Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. The datasphere is expanding at an exponential rate, and companies of all sizes are sitting on immense data stores.

Data Warehouse 52

Data Warehouse OLAP Data Lake Online Analytical Processing 52

The Data Administration Newsletter

APRIL 6, 2021

A metadata-driven data warehouse (MDW) offers a modern approach that is designed to make EDW development much more simplified and faster. It makes use of metadata (data about your data) as its foundation and combines data modeling and ETL functionalities to build data warehouses.

Metadata 52

Metadata Data Warehouse Business Intelligence IT 52