Data Virtualization

MAY 22, 2025

Reading Time: 2 minutes The data lakehouse has emerged as a powerful and popular data architecture, combining the scale of data lakes with the management features of data warehouses. It promises a unified platform for storing and analyzing structured and unstructured data, particularly for.

Data Lake

Data Virtualization

FEBRUARY 6, 2025

Additionally, storage continued to grow in capacity, epitomized by an optical disk designed to store a petabyte of data, and the global Internet population. The post Denodos Predictions for 2025 appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

Data Integration

Data Virtualization

MAY 20, 2025

Reading Time: 3 minutes Gartner has had a long history of analyzing the potential of a logical approach to data management. In 2020, in The Practical Logical Data Warehouse, Gartner begins by saying, The logical data warehouse a data consolidation and virtualization architecture.

Data Warehouse

Data Virtualization

APRIL 24, 2025

The post Financial Services Data Management Made Easy with GenAI and Denodo Platform on AWS appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information. However, many organizations face a significant hurdle: the presence of legacy.

Management

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

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 Lake

DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven

Analytics Vidhya

FEBRUARY 6, 2023

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary.

Machine Learning

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Genie — Distributed big data orchestration service by Netflix. DataOps is a hot topic in 2021.

Testing

Cloudera

MAY 17, 2021

Making a decision on a cloud data warehouse is a big deal. Modernizing your data warehousing experience with the cloud means moving from dedicated, on-premises hardware focused on traditional relational analytics on structured data to a modern platform.

Data Warehouse

DataKitchen

AUGUST 19, 2021

Each data source is updated on its own schedule, for example, daily, weekly or monthly. The DataKitchen Platform ingests data into a data lake and runs Recipes to create a data warehouse leveraged by users and self-service data analysts. The third set of domains are cached data sets (e.g., Conclusion.

Data Warehouse

Alation

JULY 28, 2022

It’s costly and time-consuming to manage on-premises data warehouses — and modern cloud data architectures can deliver business agility and innovation. However, CIOs declare that agility, innovation, security, adopting new capabilities, and time to value — never cost — are the top drivers for cloud data warehousing.

Data Warehouse

IBM Big Data Hub

AUGUST 5, 2019

In a previous blog , I explained how data science capabilities, massive parallel processing (MPP). and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?

Data Warehouse

Cloudera

FEBRUARY 9, 2021

Today’s customers have a growing need for a faster end to end data ingestion to meet the expected speed of insights and overall business demand. This ‘need for speed’ drives a rethink on building a more modern data warehouse solution, one that balances speed with platform cost management, performance, and reliability.

Data Warehouse

Data Virtualization

APRIL 21, 2022

Reading Time: 3 minutes First we had data warehouses, then came data lakes, and now the new kid on the block is the data lakehouse. But what is a data lakehouse and why should we develop one? In a way, the name describes what.

Data Lake

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. This results in less joins between the metric data in fact tables, and the dimensions. So let’s dive in! OLTP vs OLAP.

Data Warehouse

IBM Big Data Hub

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

Data Virtualization

APRIL 13, 2022

Reading Time: < 1 minute The Denodo Platform, based on data virtualization, enables a wide range of powerful, modern use cases, including the ability to seamlessly create a logical data warehouse. Logical data warehouses have all of the capabilities of traditional data warehouses, yet they.

Data Warehouse

Cloudera

SEPTEMBER 17, 2018

These trends and demands lead to stress for existing data warehouse solutions – scale, efficiency, security integrations, IT budgets, ease of access. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

Data Warehouse

Timo Elliott

JANUARY 6, 2022

Like the proverbial man looking for his keys under the streetlight , when it comes to enterprise data, if you only look at where the light is already shining, you can end up missing a lot. Modern technologies allow the creation of data orchestration pipelines that help pool and aggregate dark data silos. Data sense-making.

IT

DataRobot

JANUARY 20, 2022

Ultimately, this will free up and empower the analytical and data science health community resources to support the big clinical and operational change programmes required. Action to take. Technology Alliance. Learn More About the Snowflake and DataRobot Partnership.

Data-driven

CIO Business Intelligence

APRIL 25, 2022

Now generally available, the M&E data lakehouse comes with industry use-case specific features that the company calls accelerators, including real-time personalization, said Steve Sobel, the company’s global head of communications, in a blog post. Features focus on media and entertainment firms.

Recreation/Entertainment

Sisense

DECEMBER 3, 2019

Data is the New Oil” was coined by The Economist in May 2017 and became a mantra for organizations to drive new wealth from data. But in reality, data by itself has no value. The rapid growth of data volumes has effectively outstripped our ability to process and analyze it. Optimize raw data using materialized views.

Analytics

datapine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. BI developer skills encompass crafting and executing data-driven queries upon request as well as the ongoing technical development of a company’s BI platforms or solutions. Business Intelligence Job Roles. Yes, they exist.

Business Intelligence

Data Virtualization

JULY 1, 2021

If we look at a typical , many of its stages have more to do with data than science. Before data scientists can begin their work regarding data science, they often must begin by: Finding the right data Gaining access.

Data Science

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Overall data architecture and strategy. Cost reduction and best business practices.

Optimization

Cloudera

OCTOBER 29, 2020

Adding to these innovations, we most recently released CDP Data Visualization (DV) — A native visualization tool built from our acquisition of Arcadia Data that augments data exploration and analytics across the lifecycle to more effectively share insights across the business. Accelerate Collaboration Across The Lifecycle.

Visualization

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse

Cloudera

JULY 11, 2022

The need for data fabric. As Cloudera CMO David Moxey outlined in his blog , we live in a hybrid data world. Data is growing and continues to accelerate its growth. We look forward to speaking with you and helping you make the most of your data. It is changing in makeup and appearing in ever more places.

Data Architecture

Cloudera

OCTOBER 4, 2023

A unique architecture to optimize for real-time data warehousing and business analytics: Cloudera Data Platform (CDP) offers Apache Kudu as part of our Data Hub cloud service, providing a consistent, dependable way to support the ingestion of data streams into our analytics environment, in real time, and at any scale.

Data Warehouse

datapine

MAY 21, 2019

Also, limited resources make looking for qualified professionals such as data science experts, IT infrastructure professionals and consulting analysts impractical and worrisome. In addition to increasing the price of deployment, setting up these data warehouses and processors also impacted expensive IT labor resources.

Business Intelligence

DataRobot Blog

FEBRUARY 21, 2022

With growing pressure on data scientists, every organization needs to ensure that their teams are empowered with the right tools. Data science notebooks have become a crucial part of the data science practice. We had a lot of workarounds to address many of the issues that I’ll share later in this blog.

Data Science

Cloudera

OCTOBER 11, 2022

This leads to the obvious question – how do you do data at scale ? Al needs machine learning (ML), ML needs data science. Data science needs analytics. And they all need lots of data. Different data types need different types of analytics – real-time, streaming, operational, data warehouses.

Data Science

Cloudera

AUGUST 8, 2022

The general availability covers Iceberg running within some of the key data services in CDP, including Cloudera Data Warehouse ( CDW ), Cloudera Data Engineering ( CDE ), and Cloudera Machine Learning ( CML ). Cloudera Data Engineering (Spark 3) with Airflow enabled. Cloudera Machine Learning .

Snapshot

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence