IDC’s research has shown the movement of most IT workloads to the cloud in the coming years. Yet, with all the talk about enterprises moving to the cloud, some of them still wonder if such a move is really cost effective and what business benefits may result. While the answers to such questions vary from workload to workload, one area attracting particular attention is that of the data warehouse.
Many enterprises have substantial investments in data warehousing, with an ongoing cost to managing that resource in terms of software licensing, maintenance fees, operational costs, and hardware. Can it make sense to move to a cloud-based alternative? What are the costs and benefits? How soon can such a move pay itself off?
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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.
The enterprise data warehouse (EDW) has been at the cornerstone of enterprise data strategies for over 20 years. EDW systems have traditionally been built on relatively costly hardware infrastructures. But ever-growing data volume and increasingly complex processing have raised the cost of EDW software and hardware licenses while impacting the performance needed for analytic insights. Organizations can now use EDW offloading and optimization techniques to reduce costs of storing, processing and analyzing large volumes of data.
Getting data governance right is critical to your business success. That means ensuring your data is clean, of excellent quality, and of verifiable lineage. Such governance principles can be applied in Hadoop-like environments. Hadoop is designed to store, process and analyze large volumes of data at significantly lower cost than a data warehouse. But to get the return on investment, you must infuse data governance processes as part of offloading.
Published By: SRC,LLC
Published Date: Jun 01, 2009
Companies spend millions of dollars every year on building data warehouses, buying business intelligence (BI) software tools and managing their analytic processes in the hope of gaining consumer insight and winning market share. Yet, many companies fail to realize the full benefits of their technology investments because they are hamstrung by the layers of expertise and the complexity of technology tools needed to integrate various data warehouses and associated tools within their existing analytic environments. Since analysis is only as good as the accessibility, timeliness and accuracy of the information being analyzed, the interoperability of any data warehouse with any analytic environment is essential to achieving insightful, actionable analysis and making better decisions.
Published By: Vertica
Published Date: Feb 20, 2010
For over a decade, IT organizations have been plagued by high data warehousing costs, with millions of dollars spent annually on specialized, high-end hardware and DBA personnel overhead for performance tuning. The root cause: using data warehouse database management (DBMS) software, like Oracle and SQLServer that were designed 20-30 years ago to handle write-intensive OLTP workloads, not query-intensive analytic workloads.
A comprehensive solution for leveraging data in today's retail environment. From customer data to product placement statistics, retail organizations are constantly juggling information. As the sheer amount of data continues to grow, it becomes increasingly difficult to manage. Not only does data come in many different forms—such as reports, memos and e-mails—but often it’s scattered across multiple repositories.
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.
Published By: SnowFlake
Published Date: Jul 08, 2016
In the era of big data, enterprise data warehouse (EDW) technology continues to evolve as vendors focus on innovation and advanced features around in-memory, compression, security, and tighter integration with Hadoop, NoSQL, and cloud. Forrester identified the 10 most significant EDW software and services providers — Actian, Amazon Web Services (AWS), Hewlett Packard Enterprise (HPE), IBM, Microsoft, Oracle, Pivotal Software, SAP, Snowflake Computing, and Teradata — in the category and researched, analyzed, and scored them. This report details our findings about how well each vendor fulfills our criteria and where they stand in relation to each other to help enterprise architect professionals select the right solution to support their data warehouse platform.
Read how Splunk enabled WhitePages, the largest on-line directory of people and businesses, to protect the site's content and the brand by monitoring abusive site traffic and learn how Splunk's in-house search eliminated a data warehouse investment.
Published By: Matillion
Published Date: May 12, 2011
This whitepaper explains the importance of Business Intelligence to midsize companies, examines the challenges found in BI projects and explains how to be successful in improving visibility in your business.
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