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

AWS Machine Learning Blog

OCTOBER 24, 2024

Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it cost-effective to efficiently analyze all your data using your existing business intelligence tools. Amazon QuickSight powers data-driven organizations with unified (BI) at hyperscale. A SageMaker domain.

Data Warehouse 115

Data Warehouse Machine Learning Machine Learning Cloud Data 115

databricks

JUNE 18, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

AI 205

AI AI Data Science Artificial Intelligence 205

databricks

JUNE 11, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

Database 214

Database Data Lakes ETL Analytics 214

KDnuggets

JUNE 19, 2025

Blog Top Posts About Topics AI Career Advice Computer Vision Data Engineering Data Science Language Models Machine Learning MLOps NLP Programming Python SQL Datasets Events Resources Cheat Sheets Recommendations Tech Briefs Advertise Join Newsletter Go vs. Python for Modern Data Workflows: Need Help Deciding?

Python 283

Python Natural Language Processing Data Science Machine Learning 283

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

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 135

Data Lakes Data Warehouse Big Data Big Data 135

Dataversity

DECEMBER 18, 2023

Analytics at the core is using data to derive insights for measuring and improving business performance [1]. To enable effective management, governance, and utilization of data and analytics, an increasing number of enterprises today are looking at deploying the data catalog, semantic layer, and data warehouse.

Data Warehouse 119

Data Warehouse Analytics Analytics 119

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

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

Data Science Dojo

FEBRUARY 1, 2023

Introduction Dedicated SQL pools offer fast and reliable data import and analysis, allowing businesses to access accurate insights while optimizing performance and reducing costs. DWUs (Data Warehouse Units) can customize resources and optimize performance and costs.

Azure 195

Azure SQL Analytics Analytics 195

Data Science Dojo

MARCH 27, 2025

Thats where data normalization comes in. Its a structured process that organizes data to reduce redundancy and improve efficiency. Whether you’re working with relational databases, data warehouses , or machine learning pipelines, normalization helps maintain clean, accurate, and optimized datasets. Simple, right?

Database 195

Database Data Warehouse Machine Learning Machine Learning 195

databricks

JUNE 4, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

AWS 130

AWS AI AI Data Science 130

Dataversity

SEPTEMBER 24, 2021

We have seen an unprecedented increase in modern data warehouse solutions among enterprises in recent years. Experts believe that this trend will continue: The global data warehousing market is projected to reach $51.18 The reason is pretty obvious – businesses want to leverage the power of data […].

Data Warehouse 97

Data Warehouse Data Quality Data Governance Cloud Data 97

Smart Data Collective

JUNE 6, 2021

While you may think that you understand the desires of your customers and the growth rate of your company, data-driven decision making is considered a more effective way to reach your goals. The use of big data analytics is, therefore, worth considering—as well as the services that have come from this concept, such as Google BigQuery.

Big Data Analytics 137

Big Data Analytics Big Data Analytics Big Data Big Data 137

Dataversity

DECEMBER 7, 2020

Data warehousing (DW) and business intelligence (BI) projects are a high priority for many organizations who seek to empower more and better data-driven decisions and actions throughout their enterprises. These groups want to expand their user base for data discovery, BI, and analytics so that their business […].

Data Warehouse 90

Data Warehouse Business Intelligence Business Intelligence Analytics 90

Analytics Vidhya

FEBRUARY 6, 2023

To make these processes efficient, data pipelines are necessary. Data engineers specialize in building and maintaining these data pipelines that underpin the analytics ecosystem. In this blog, we will […] The post How to Implement a Data Pipeline Using Amazon Web Services?

Data Pipeline 271

Data Pipeline Data Engineering Data Engineer Data Engineering 271

Data Science Dojo

SEPTEMBER 6, 2023

M aintaining the security and governance of data within a data warehouse is of utmost importance. Data Security: A Multi-layered Approach In data warehousing, data security is not a single barrier but a well-constructed series of layers, each contributing to protecting valuable information.

Data Warehouse 195

Data Warehouse Data Governance ETL Data Quality 195

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. The cloud is no longer synonymous with risk. What do you migrate, how, and when?

Data Warehouse 69

Data Warehouse Cloud Data Data Governance Database 69

AWS Machine Learning Blog

JUNE 12, 2025

In this post, we illustrate how VideoAmp , a media measurement company, worked with the AWS Generative AI Innovation Center (GenAIIC) team to develop a prototype of the VideoAmp Natural Language (NL) Analytics Chatbot to uncover meaningful insights at scale within media analytics data using Amazon Bedrock.

Analytics 106

Analytics Analytics SQL Data Warehouse 106

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Pickl AI

FEBRUARY 23, 2023

Organisations must store data in a safe and secure place for which Databases and Data warehouses are essential. You must be familiar with the terms, but Database and Data Warehouse have some significant differences while being equally crucial for businesses. What is Data Warehouse?

Data Warehouse 52

Data Warehouse Database Data Analysis Data Analysis 52

IBM Journey to AI blog

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

Data Warehouse 112

Data Warehouse Data Lakes Big Data Database 112

Pickl AI

FEBRUARY 3, 2025

Summary: A Data Warehouse consolidates enterprise-wide data for analytics, while a Data Mart focuses on department-specific needs. Data Warehouses offer comprehensive insights but require more resources, whereas Data Marts provide cost-effective, faster access to focused data.

Data Warehouse 52

Data Warehouse Analytics Analytics Database 52

Pickl AI

JUNE 11, 2024

Summary: A data warehouse is a central information hub that stores and organizes vast amounts of data from different sources within an organization. Unlike operational databases focused on daily tasks, data warehouses are designed for analysis, enabling historical trend exploration and informed decision-making.

Data Warehouse 52

Data Warehouse ETL Data Mining Data Mining 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

JUNE 15, 2023

The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Moreover, increased regulatory requirements make it harder for enterprises to democratize data access and scale the adoption of analytics and artificial intelligence (AI).

Data Warehouse 110

Data Warehouse Data Lakes Cloud Data Analytics 110

Dataversity

MARCH 10, 2023

Most companies utilize AI only for the tiniest fraction of their data because scaling AI is challenging. Typically, enterprises cannot harness the power of predictive analytics because they don’t have a fully mature data strategy.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Predictive Analytics 52

phData

NOVEMBER 4, 2024

The modern data stack is defined by its ability to handle large datasets, support complex analytical workflows, and scale effortlessly as data and business needs grow. Two key technologies that have become foundational for this type of architecture are the Snowflake AI Data Cloud and Dataiku.

Machine Learning 69

Machine Learning Machine Learning Data Science Data Preparation 69

AWS Machine Learning Blog

APRIL 3, 2025

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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AWS Data Governance Data Silos SQL 100

Dataversity

DECEMBER 11, 2023

Organizations learned a valuable lesson in 2023: It isn’t sufficient to rely on securing data once it has landed in a cloud data warehouse or analytical store. As a result, data owners are highly motivated to explore technologies in 2024 that can protect data from the moment it begins its journey in the source systems.

Data Governance 111

Data Governance Data Warehouse Cloud Data Analytics 111

Dataversity

SEPTEMBER 5, 2024

… and your data warehouse / data lake / data lakehouse. A few months ago, I talked about how nearly all of our analytics architectures are stuck in the 1990s. Maybe an executive at your company read that article, and now you have a mandate to “modernize analytics.”

Analytics 52

Analytics Analytics Data Lakes Data Warehouse 52

Alation

AUGUST 9, 2021

percent) cite culture – a mix of people, process, organization, and change management – as the primary barrier to forging a data-driven culture, it is worth examining data democratization efforts within your organization and the business user’s experience throughout the data analytics stack.

Analytics 98

Analytics Analytics Data Warehouse Data Scientist 98

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

AWS Machine Learning Blog

DECEMBER 16, 2024

Were seeing a remarkable convergence of data, analytics, and generative AI. Now they can access databases and data warehouses, as well as unstructured business data, like emails, reports, charts, graphs, and images. About the author Swami Sivasubramanian is VP, AWS AI & Data. And now, it still is.

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AWS AI AI Data Warehouse 104

AWS Machine Learning Blog

OCTOBER 28, 2024

The workflow includes the following steps: Within the SageMaker Canvas interface, the user composes a SQL query to run against the GCP BigQuery data warehouse. Athena returns the queried data from BigQuery to SageMaker Canvas, where you can use it for ML model training and development purposes within the no-code interface.

Machine Learning 110

Machine Learning Machine Learning ML ML 110