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Documents related to » expensive data warehouse bi


About Big Data
There may not be a consensus with respect to just how big

expensive data warehouse bi  warehouse can rapidly become expensive as the data volume increases. Scaling a data warehouse can be a burden when you’re dealing with such volumes. Meanwhile, some big data providers can produce solutions not only that are cheaper from the get go, but which can be escalated, adapted, and modified as required. Open source solutions—such as NoSQL—have also played an important role in the big data movement, forcing market prices to stay down. The Players As with any other segment in the software Read More...
How to Evaluate Web-based BI Solutions
Web-based business intelligence (BI) is no longer an anomaly: organizations are ready for BI solutions that go beyond Web portals. However, when selecting Web

expensive data warehouse bi  less invasive, and less expensive ways to benefit from reporting and analytics. Although most organizations implement traditional BI applications, use of the Internet to collaborate and to deliver reporting and OLAP is already a main element of software deployments. As the demand for Web 2.0, software as a service (SaaS), service-oriented architecture (SOA), and hosted applications has increased, organizations are increasingly examining Web-based applications. There are two approaches to Web-based BI Read More...
Access to Critical Business Intelligence: Challenging Data Warehouses?
There is a perception that if business users are given access to enterprise databases and raw query tools, they will create havoc in the system, which is a

expensive data warehouse bi  can be far less expensive, while adequately effective, than building and maintaining a redundant DW. Further, the IT management costs of tuning the transaction database are likely less than the cost of the ongoing maintenance required by a DW, which becomes a mission on its own, to a degree that the enterprises even forgot the original purpose of the DW. Part Six of the Business Intelligence Report Status Quo series. Improving the DW Model When the DW model was conceived, it was believed that it was Read More...
Data, Data Everywhere: A Special Report on Managing Information
The quantity of information in the world is soaring. Merely keeping up with, and storing new information is difficult enough. Analyzing it, to spot patterns and

expensive data warehouse bi  than having to buy expensive equipment. Amazon, Google and Microsoft are the most prominent firms to make their massive computing infrastructure available to clients. As more corporate functions, such as human resources or sales, are managed over a network, companies can see patterns across the whole of the business and share their information more easily. A free programming language called R lets companies examine and present big data sets, and free software called Hadoop now allows ordinary PCs to Read More...
The Necessity of Data Warehousing
An explanation of the origins of data warehousing and why it is a crucial technology that allows businesses to gain competitive advantage. Issues regarding

expensive data warehouse bi  Storage Device) were extremely expensive on a per-megabyte basis. Therefore, much of the needed data was stored offline, typically on magnetic tape. Processing power was very expensive as measured in MIPS (Millions of Instructions per Second). Mainframes had to reserve most of their processing power for day-to-day operations, reports could only be run overnight in batch mode (without interaction from the user). Relational database technology was still in its infancy, and server engines were not powerful Read More...
Data Quality Trends and Adoption
While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ

expensive data warehouse bi  Quality Trends and Adoption While much of the interest in data quality (DQ) solutions had focused on avoiding failure of data management-related initiatives, organizations now look to DQ efforts to improve operational efficiencies, reduce wasted costs, optimize critical business processes, provide data transparency, and improve customer experiences. Read what DQ purchase and usage trends across UK and US companies reveal about DQ goals and drivers. Read More...
Oracle Warehouse Builder: Better Late than Never?
Close to a year behind schedule, Oracle released Warehouse Builder to the market. Oracle, in an interesting contradiction in terms, has stated that the product

expensive data warehouse bi  Warehouse Builder: Better Late than Never? Event Summary REDWOOD SHORES, Calif., Mar. 6, 2000 - Oracle announced the immediate availability of Oracle Warehouse Builder, an extensible and easy-to-use data warehouse design and deployment framework. As part of Oracle''s Intelligent WebHouse Initiative, Oracle Warehouse Builder automates much of the work that goes into creating a powerful, single data store for e-business analysis, specifically with its ability to integrate historical data with the Read More...
Addressing the Complexities of Remote Data Protection
As companies expand operations into new markets, the percentage of total corporate data in remote offices is increasing. Remote offices have unique backup and

expensive data warehouse bi  replication can be less expensive than mirroring. It may offer a superior solution over long distances, and allows for many-to-one consolidation of data from remote offices to a central site. However, both mirroring and replication can be ineffective solutions for individual data loss or corruption. Any loss would be replicated to the backup system, leaving you with two bad copies of your data. These solutions are best suited to system-level recovery. Continuous data protection , or CDP, takes the benefit Read More...
2013 Big Data Opportunities Survey
While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry

expensive data warehouse bi  Big Data Opportunities Survey While big companies such as Google, Facebook, eBay, and Yahoo! were the first to harness the analytic power of big data, organizations of all sizes and industry groups are now leveraging big data. A survey of 304 data managers and professionals was conducted by Unisphere Research in April 2013 to assess the enterprise big data landscape, the types of big data initiatives being invested in by companies today, and big data challenges. Read this report for survey responses Read More...
Warehouse Management Systems by the Numbers
When it comes to warehouse management systems (WMS), the stats are both shocking and thought-provoking. And although you don''t see these stats in the marketing

expensive data warehouse bi  Management Systems by the Numbers Warehouse Management Systems by the Numbers Featured Author - Ren Jones - September 22, 2006 Warehouses are built around numbers—from the facility''s square footage, to how many rows of racking it takes to stock the number of stock-keeping units (SKUs), all the way to the amount of orders processed through a facility in a day. This article takes the numbers associated with warehouse management systems (WMS) you don''t see in the marketing brochures or Read More...
Are you BI Lingual or Just BI Curious?
Lost in TranslationIf your organization was a celebutante, who would it be? Well, comely or not, let’s hope that when it comes to BI, you’re not a bemused

expensive data warehouse bi  you BI Lingual or Just BI Curious? Lost in Translation If your organization was a celebutante, who would it be? Well, comely or not, let’s hope that when it comes to BI, you’re not a bemused, glassy-eyed Scarlett Johansson à la Lost in Translation http://www.imdb.com/title/tt0335266 . If so, there’s a cure and it’s not acting lessons. It’s a lesson in collaboration; ensuring that both your IT and business teams are speaking the same language so that technology is aligned with your core Read More...
Enterprise Data Management: Migration without Migraines
Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an

expensive data warehouse bi  Data Management: Migration without Migraines Moving an organization’s critical data from a legacy system promises numerous benefits, but only if the migration is handled correctly. In practice, it takes an understanding of the entire ERP data lifecycle combined with industry-specific experience, knowledge, and skills to drive the process through the required steps accurately, efficiently, and in the right order. Read this white paper to learn more. Read More...
Data Management and Analysis
From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it

expensive data warehouse bi  Management and Analysis From a business perspective, the role of data management and analysis is crucial. It is not only a resource for gathering new stores of static information; it is also a resource for acquiring knowledge and supporting the decisions companies need to make in all aspects of economic ventures, including mergers and acquisitions (M&As). For organizational growth, all requirements and opportunities must be accurately communicated throughout the value chain. All users—from end users Read More...
Data Center Projects: Advantages of Using a Reference Design
It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete

expensive data warehouse bi  Center Projects: Advantages of Using a Reference Design It is no longer practical or cost-effective to completely engineer all aspects of a unique data center. Re-use of proven, documented subsystems or complete designs is a best practice for both new data centers and for upgrades to existing data centers. Adopting a well-conceived reference design can have a positive impact on both the project itself, as well as on the operation of the data center over its lifetime. Reference designs simplify and Read More...
Data Pro Accounting Software
Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the

expensive data warehouse bi  Pro Accounting Software Data Pro Accounting Software, Inc., privately owned, is based in St. Petersburg, Florida and was originally incorporated in June of 1985. The goal of the corporation has always been to develop and market a full line of accounting software products for a wide range of market segments, on a broad spectrum of operating systems environments such as DOS, Windows and UNIX. Read More...

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