data warehouses

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Hadoop and the Data Warehouse: Competitive or Complementary?

Published By: Teradata     Published Date: Jan 30, 2015
It is hard for data and IT architects to understand what workloads should move, how to coordinate data movement and processing between systems, and how to integrate those systems to provide a broader and more flexible data platform. To better understand these topics, it is helpful to first understand what Hadoop and data warehouses were designed for and what uses were not originally intended as part of the design.
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teradata, data, big, data, analytics. insights, solutions, business opportunities, challenges, technology, framework, apache, hadoop, architecture, warehouse, optimization, security, scalability, consistency, flexibility, data management
    
Teradata

How to Maximize the Potential of Your Big Data

Published By: SAS     Published Date: Nov 10, 2014
Learn how this upcoming year should be the year you make your big data actionable and see what else you should be doing to maximize its potential.
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sas, data integration, data evolution, comprehensive data, data management, data virtualization, data warehouses, data profiling, metadata management, best practices, business intelligence, data center
    
SAS

IDC Research Spotlight: Data Warehouses Ascend to the Cloud

Published By: Teradata     Published Date: May 02, 2017
Should the data warehouse be deployed on the cloud? Read this IDC Research Spotlight to learn more.
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data warehouse, data storage, data management, data analytics, data preparation, data integration, system integration
    
Teradata

IDC Security Paper: Securing the Datacenter from Advanced Threats

Published By: Juniper Networks     Published Date: Oct 19, 2015
Datacenters are the factories of the Internet age, just like warehouses, assembly lines, and machine shops were for the industrial age. Over the course of the past several years, riding the wave of modernization, datacenters have become the heart and soul of the financial industry, which each year invests over $480 billion in datacenter infrastructure of hardware, software, networks, and security and services.
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juniper, datacenter, threat, ciso, enterprise, data, customer
    
Juniper Networks

Information and Data Management Solutions Generate Value

Published By: AWS - ROI DNA     Published Date: Jun 12, 2018
Traditional databases and data warehouses are evolving to capture new data types and spread their capabilities in a hybrid cloud architecture, allowing business users to get the same results regardless of where the data resides. The details of the underlying infrastructure become invisible. Self-managing data lakes automate the provisioning, reliability, performance and cost, enabling data access and experimentation.
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AWS - ROI DNA

Media Buy Agility: Snowflake Computing Empowers Accordant Media’s Optimized Media Purchasing

Published By: SnowFlake     Published Date: Jul 08, 2016
This EMA case study profiles the implementation of the Snowflake Elastic Data Warehouse, a new generation of cloud-based data warehouses, by Accordant Media. This document details significant tangible and intangible improvements and opportunities the Snowflake solution created for the Accordant Media infrastructure and analytical teams.
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snowflake, media, data, technology, cloud-based data, best practices, business intelligence, productivity, business technology
    
SnowFlake

Optimizing Customer Engagement Through Connected Data

Published By: RedPoint Global     Published Date: May 11, 2017
While they’re intensifying, business-data challenges aren’t new. Companies have tried several strategies in their attempt to harness the power of data in ways that are feasible and effective. The best data analyses and game-changing insights will never happen without the right data in the right place at the right time. That’s why data preparation is a non-negotiable must for any successful customer-engagement initiative. The fact is, you can’t simply load data from multiple sources and expect it to make sense. This white paper examines the shortcomings of traditional approaches such as data warehouses/data lakes and explores the power of connected data.
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customer engagement, marketing data, marketing data analytics, customer data platform
    
RedPoint Global

Oracle Autonomous Data Warehouse Cloud

Published By: Oracle     Published Date: Nov 28, 2017
Today’s leading-edge organizations differentiate themselves through analytics to further their competitive advantage by extracting value from all their data sources. Other companies are looking to become data-driven through the modernization of their data management deployments. These strategies do include challenges, such as the management of large growing volumes of data. Today’s digital world is already creating data at an explosive rate, and the next wave is on the horizon, driven by the emergence of IoT data sources. The physical data warehouses of the past were great for collecting data from across the enterprise for analysis, but the storage and compute resources needed to support them are not able to keep pace with the explosive growth. In addition, the manual cumbersome task of patch, update, upgrade poses risks to data due to human errors. To reduce risks, costs, complexity, and time to value, many organizations are taking their data warehouses to the cloud. Whether hosted lo
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Oracle

Oracle Exadata Case Study: TDWI "What Works" Reprint

Published By: Oracle Corporation     Published Date: May 11, 2012
This white paper presents two case studies that illustrate how Oracle Exadata increased storage capacity for data warehouses by 150%, reduced operational and database running costs by 50%, and on average improved database query performance by 10x.
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oracle, data warehousing, database, exadata, database machine, infrastructure, operation, operation costs, mobile, growth, payback, architecture, demands, enterprise applications, data management, cloud computing, design and facilities
    
Oracle Corporation

Por que os clientes estão migrando seus data warehouses para a nuvem?

Published By: Oracle     Published Date: Apr 16, 2018
A velocidade e o volume de entrada de dados estão gerando demandas esmagadoras sobre os data marts tradicionais, os data warehouses e os sistemas analíticos. Uma solução em nuvem de data warehouse tradicional pode ajudar os clientes a suprirem tais demandas? Muitos clientes estão comprovando o valor dos data warehouses na nuvem através dos ambientes de testes ou de inovação, dos data marts na área de negócios e backup de banco de dados.
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clientes, estao, migrando, data, warehouses, nuvem
    
Oracle

Real-Time Analytics

Published By: Oracle PaaS/IaaS/Hardware     Published Date: Jul 25, 2017
"With the introduction of Oracle Database In-Memory and servers with the SPARC S7 and SPARC M7 processors Oracle delivers an architecture where analytics are run on live operational databases and not on data subsets in data warehouses. Decision-making is much faster and more accurate because the data is not a stale subset. And for those moving enterprise applications to the cloud, Real-time analytics of the SPARC S7 and SPARC M7 processors are available both in a private cloud on SPARC servers or in Oracle’s Public cloud in the SPARC cloud compute service. Moving to the Oracle Public Cloud does not compromise the benefits of SPARC solutions. Some examples of utilizing real time data for business decisions include: analysis of supply chain data for order fulfillment and supply optimization, analysis of customer purchase history for real time recommendations to customers using online purchasing systems, etc. "
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Oracle PaaS/IaaS/Hardware

Realize Unparalleled Business Value from Enterprise Data

Published By: DataFlux     Published Date: Jan 07, 2011
This white paper introduces and examines a breakthrough platform solution designed to drive parallel-process data integration - without intensive pre-configuration - and support full-lifecycle data management from discovery to retirement.
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dataflux, enterprise data, data integration, configuration, lifecycle data management, data warehouses, enterprise software, product lifecycle management, application integration, configuration management, data quality, data warehousing
    
DataFlux

Scaling Data Integration to Handle Big Data

Published By: IBM     Published Date: Mar 30, 2017
In today’s competitive on-line world, the speed of change in customer behaviour is increasing. In addition, in industries such as retail banking, car insurance and to some extent retail, the Internet has become the dominant way in which customers interact with an organisation. Yet in many data warehouses today, being able to analyse customer on-line behaviour is often not possible because the clickstream web log data needed to do this is missing. It is a key point because customer access to the web has made loyalty cheap.
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cyber attacks, data protection, it security, security solutions, system protector, web security, analytics
    
IBM

Simple is STILL Better: Embrace Speed & Simplicity for a competitive edge

Published By: IBM     Published Date: Nov 16, 2015
The market offers an array of choices to organizations planning new data warehouses to manage large and varied data sets. Most vendors emphasize the speed of their products, but few address the real need: to increase speed efficiently, which reduces complexity and cost by simplifying data warehousing.
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ibm, organization, puredata, analytics, research, data warehouse, knowledge management, data management, business technology
    
IBM

Snowflake Elastic Data Warehouse

Published By: SnowFlake     Published Date: Jul 08, 2016
Data today comes from diverse sources in diverse forms and needs to be analyzed by ever more users as quickly as possible. Those demands are stressing the limitations of traditional data warehouses and data platforms. Snowflake has reinvented the data warehouse, making it possible to bring all your business data together in a single system that can support all your users and workloads. Built from the cloud up as a software service, Snowflake eliminates the cost, complexity, and inflexibility of existing solutions while allowing you to use the tools and skills you already have.
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snowflake, data, technology, best practices, solutions, cloud support, storage, business intelligence, business technology, cloud computing
    
SnowFlake

Squeezing More Value Out of Data Warehouses through the Power of Database Compression

Published By: Vertica     Published Date: Mar 15, 2010
In a world of growing data volumes and shrinking IT budgets, it is critical to think differently about the efficiency of your database and storage infrastructure. The Vertica Analytic Database is a high-performance, scalable and cost-effective solution that can bring dramatic savings in hardware, storage and operational costs.
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vertica, ec2, cdr, elastic, saas, cdr, cloud computing, data management, ad-hoc, business intelligence, cloud, cloudbased applications, analytic, saas, dbms, mpp, storage management, business analytics, business metrics, marketing automation
    
Vertica

Successful Data Warehouse Approaches to Meet Today's Analytics Demands

Published By: IBM     Published Date: Nov 08, 2017
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
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data warehouse, analytics, ibm, deployment models
    
IBM

Successful Data Warehouse Approaches to Meet Today's Analytics Demands

Published By: Group M_IBM Q1'18     Published Date: Jan 23, 2018
In this paper, you'll learn how organizations are adopting increasingly sophisticated analytics methods, that analytics usage trends are placing new demands on rigid data warehouses, and what's needed is hybrid data warehouse architecture that supports all deployment models.
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data warehouse, analytics, hybrid data warehouse, development model
    
Group M_IBM Q1'18

The Best-in-Class Data Warehouse: Fast, Simple, Impactful (Aberdeen White Paper)

Published By: IBM     Published Date: Jan 14, 2015
Decision makers need data and they need it now. As the pace of business continues to accelerate, organizations are leaning heavily on data warehouses to deliver analytical grist for the mill of daily decisions. This Research Report from Aberdeen Group examines the benefits of data warehouse solutions that offer rapid information delivery while minimizing complexity for users and IT.
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aberdeen group, data warehouse, data center, data management, analytic tools, collaboration, data trust, data analytics, business intelligence
    
IBM

The Economic Advantages of Google BigQuery versus Alternative Cloud-based EDW Solutions

Published By: Google     Published Date: Nov 04, 2019
"ESG compared Google BigQuery’s serverless Enterprise data warehouses (EDW) solution with some alternative EDW services offered by AWS, Microsoft, and Snowflake. While all of these offerings provide significant cost savings, reduction in complexity, and increased business agility when compared with an on-premises EDW solution, there are some significant differences between the offerings. Read The Economic Advantages of Google BigQuery versus Alternative Cloud-based EDW Solutions to learn more. "
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database servers, cloud database, application infrastructure, cloud database, data integration
    
Google

The Smarter Way to Manage Data

Published By: Oracle EMEA     Published Date: Apr 15, 2019
Oracle Autonomous Data Warehouse Cloud is more than just a new way to store and analyze data; it’s a whole new approach to getting more value from your data. Market leaders in every industry depend on analytics to reach new customers, streamline business processes, and gain a competitive edge. Data warehouses remain at the heart of these business intelligence (BI) initiatives, but traditional data-warehouse projects are complex undertakings that take months or even years to deliver results. Relying on a cloud provider accelerates the process of provisioning data-warehouse infrastructure, but in most cases database administrators (DBAs) still have to install and manage the database platform, then work with the line-of-business leaders to build the data model and analytics. Once the warehouse is deployed—either on premises or in the cloud—they face an endless cycle of tuning, securing, scaling, and maintaining these analytic assets. Oracle has a better way. Download this whitepaper to f
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Oracle EMEA

Transforming from Passive Data Catalogs to Active Data Hubs

Published By: Zaloni     Published Date: Apr 24, 2019
Why your data catalog won’t deliver significant ROI According to Gartner, organizations that provide access to a curated catalog of internal and external data assets will derive twice as much business value from their analytics investments by 2020 than those that do not. That’s a ringing endorsement of data catalogs, and a growing number of enterprises seem to agree. In fact, the global data catalog market is expected to grow from US$210.0 million in 2017 to US$620.0 million by 2022, at a Compound Annual Growth Rate (CAGR) of 24.2%. Why such large and intensifying demand for data catalogs? The primary driver is that many organizations are working to modernize their data platforms with data lakes, cloud-based data warehouses, advanced analytics and various SaaS applications in order to grow profitable digital initiatives. To support these digital initiatives and other business imperatives, organizations need more reliable, faster access to their data. However, modernizing data plat
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Zaloni

Unifying Analytics Across Warehouse, Lake and Into the Cloud

Published By: Gigaom     Published Date: Sep 16, 2019
We’ve heard it before. A data warehouse is a place for formally-structured, highly-curated data, accommodating recurring business analyses, whereas data lakes are places for “raw” data, serving analytic workloads, experimental in nature. Since both conventional and experimental analysis is important in this data-driven era, we’re left with separate repositories, siloed data, and bifurcated skill sets. Or are we? In fact, less structured data can go into your warehouse, and since today’s data warehouses can leverage the same distributed file systems and cloud storage layers that host data lakes, the warehouse/lake distinction’s very premise is rapidly diminishing. In reality, business drivers and business outcomes demand that we abandon the false dichotomy and unify our data, our governance, our analysis, and our technology teams. Want to get this right? Then join us for a free 1-hour webinar from GigaOm Research. The webinar features GigaOm analyst Andrew Brust and special guest, Dav
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Gigaom

¿Por qué los clientes trasladan sus data warehouses a la nube?

Published By: Oracle     Published Date: Apr 16, 2018
La velocidad y el volumen de los datos entrantes están dando lugar a una gran demanda en los centros de datos tradicionales, repositorios de datos empresariales y sistemas analíticos. ¿Puede una solución de almacén de datos tradicional en la nube ayudar a los clientes a satisfacer estas demandas? Muchos clientes están comprobando el valor de los repositorios de datos en la nube a través de entornos “de prueba”, repositorios de datos según el área de negocios y respaldos de base de datos.
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clientes, trasladan, sus, data, warehouses
    
Oracle
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