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Software Functionality Revealed in Detail
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 bi data warehousing analysis

Software Functionality Revealed in Detail

We’ve opened the hood on every major category of enterprise software. Learn about thousands of features and functions, and how enterprise software really works.

Get free sample report
Compare Software Solutions

Visit the TEC store to compare leading software by functionality, so that you can make accurate and informed software purchasing decisions.

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Reporting and Analysis, Analytics, Data Warehousing, Workflow, Data Integration, Support, and System Requirements  

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Documents related to » bi data warehousing analysis

Thinking Radically about Data Warehousing and Big Data: Interview with Roger Gaskell, CTO of Kognitio


Managing data—particularly in large numbers—still is and probably will be the number one priority for many organizations in the upcoming years. Many of the traditional ways to store and analyze large amounts of data are being replaced with new technologies and methodologies to manage the new volume, complexity, and analysis requirements. These include new ways of developing data warehousing, the

bi data warehousing analysis  systems as well the BI and the data warehouse space in general. Roger Gaskell is responsible for all the product development that goes on at Kognitio. Prior to Kognitio, Mr. Gaskell worked as a test development manager at AB Electronics, primarily for the development and testing of the first mass production of IBM personal computers. 1.    Hello, Mr. Gaskell. Could you give us a brief introduction to Kognitio and the products the company offers? Certainly. Kognitio is a technology software vendor that Read More

Oracle Database 11g for Data Warehousing and Business Intelligence


Oracle Database 11g is a database platform for data warehousing and business intelligence (BI) that includes integrated analytics, and embedded integration and data-quality. Get an overview of Oracle Database 11g’s capabilities for data warehousing, and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data.

bi data warehousing analysis  and learn how Oracle-based BI and data warehouse systems can integrate information, perform fast queries, scale to very large data volumes, and analyze any data. Read More

Uncovering Insight Hidden in Text: How Unstructured Data Analysis Is Helping IT Deliver Knowledge


With business units demanding more access to corporate data, IT is pressured to deliver. Yet current business intelligence (BI) and data warehouse systems only examine specific quantifiable data. Find out how IT professionals can gain a better understanding of how to integrate key information from text-based sources, such as forms, e-mail, blogs, and research into their data warehouse environment to enhance BI.

bi data warehousing analysis  Yet current business intelligence (BI) and data warehouse systems only examine specific quantifiable data. Find out how IT professionals can gain a better understanding of how to integrate key information from text-based sources, such as forms, e-mail, blogs, and research into their data warehouse environment to enhance BI. Read More

Microsoft Goes Their Own Way with Data Warehousing Alliance 2000


Microsoft Corp. (Nasdaq: MSFT) today announced that 47 applications and tools from 39 vendors throughout the industry have qualified for Microsoft« Data Warehousing Alliance 2000. Alliance members and partners are committed to delivering tools and applications based on the Microsoft Data Warehousing Framework 2000, an open architecture based on the open standards and services built into the Windows« 2000 operating system, Microsoft SQL Server 7.0 and Office 2000.

bi data warehousing analysis  open, published protocols for interoperability and integrated end-to-end data warehousing services. It utilizes technologies provided in Microsoft Office 2000 and Microsoft SQL Server 7.0 products, and a partnership with Data Warehousing Alliance members for complementary tools and applications. The DWF enables data warehousing solutions where the data comes from virtually any source and where any type of information can be delivered to any compliant client interface or application. Market Impact Once Read More

A Definition of Data Warehousing


There is a great deal of confusion over the meaning of data warehousing. Simply defined, a data warehouse is a place for data, whereas data warehousing describes the process of defining, populating, and using a data warehouse. Creating, populating, and querying a data warehouse typically carries an extremely high price tag, but the return on investment can be substantial. Over 95% of the Fortune 1000 have a data warehouse initiative underway in some form.

bi data warehousing analysis  the data properly. The BI tools need the metadata for similar reasons. Summary: Data Warehousing is a complex field, with many vendors vying for market awareness. The complexity of the technology and the interactions between the various tools, and the high price points for the products require companies to perform careful technology evaluation before embarking on a warehousing project. However, the potential for enormous returns on investment and competitive advantage make data warehousing difficult to Read More

The New Virtual Data Centre


Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward.

bi data warehousing analysis  New Virtual Data Centre Old-style, one application per physical server data centers are not only nearing the end of their useful lives, but are also becoming barriers to a business’ future success. Virtualization has come to the foreground, yet it also creates headaches for data center and facilities managers. Read about aspects of creating a strategy for a flexible and effective data center aimed to carry your business forward. Read More

Meet PCI DSS Compliance Requirements for Test Data with Data Masking


Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more.

bi data warehousing analysis  PCI DSS Compliance Requirements for Test Data with Data Masking Whether you’re working toward your first or your next payment card industry (PCI) data security standard (DSS) audit, you know compliance is measured on a sliding scale. But full compliance can’t be achieved with just one policy or technology. Using data masking, a technology that alters sensitive information while preserving realism, production data can be eliminated from testing and development environments. Learn more. Read More

Garbage in, Garbage out: Getting Good Data out of Your BI Systems


Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems.

bi data warehousing analysis  Data out of Your BI Systems Garbage in, garbage out. Poor quality data leads to bad business decisions. You need high quality data in your business intelligence (BI) system to facilitate effective analysis—to make the right decisions at the right time. But how do you achieve this? Find out in Garbage In, Garbage Out: Getting Good Data Out of Your BI Systems . In this Focus Brief , you''ll learn about the steps in the data delivery cycle, the problems can occur at each step, and the metrics you can use Read More

Fundamentals of Managing the Data Center Life Cycle for Owners


Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and offers practical advice to facility owners and management.

bi data warehousing analysis  of Managing the Data Center Life Cycle for Owners Just as good genes do not guarantee health and well-being, a good design alone does not ensure a data center is well built and will remain efficient and available over the course of its life span. For each phase of the data center’s life cycle, proper care and action must be taken to continuously meet the business needs of the facility. This paper describes the five phases of the data center life cycle, identifies key tasks and pitfalls, and Read More

Effective Inventory Analysis: the 5 Key Measurements


The white paper effective inventory analysis isolates and walks you through five simple measurements that will help you ensure you are maximizing t...

bi data warehousing analysis  you are maximizing the profitability and productivity of your investment in inventory. Each measurement can be applied to a single item, a specific product line, the entire stock of a warehouse, or your entire inventory. And these five key measurements can also be used to track the improvement in your inventory performance over time. To keep your inventory performance analysis simple, accurate, and relevant, download the white paper Effective Inventory Analysis today. Because without meaningful analysis, Read More

Data Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox


Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data warehouse.

bi data warehousing analysis  Evolution: Why a Comprehensive Data Management Platform Supersedes the Data Integration Toolbox Today’s organizations have incredible amounts of information to be managed, and in many cases it is quickly spiraling out of control. To address the emerging issues around managing, governing, and using data, organizations have been acquiring quite a toolbox of data integration tools and technologies. One of the core drivers for these tools and technologies has been the ever-evolving world of the data 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 recovery requirements in order to support a wide range of applications, and to protect against a wide range of risk factors. Discover solutions that help organizations protect remote data and offer extensive data protection and recovery solutions for remote offices.

bi data warehousing analysis  impact the performance and availability of the applications to perform the backup. Your mission-critical applications require the highest degree of protection and availability. For these systems, you should look for a solution that limits the amount of data you might lose, as well as the amount of time it takes to recover when something goes wrong. Risks There are many risks that can threaten your remote data (see Figure 3). First, there is the simple and all-too-often case of someone losing a file or 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 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.

bi data warehousing analysis  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

Transactional Data: Driving Real-Time Business


A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more.

bi data warehousing analysis  Data: Driving Real-Time Business A global survey of IT leaders shows that most organizations find it challenging to convert high volumes of fresh transactional data into knowledge that business users can efficiently access, understand, and act on. SAP and HP are tackling this challenge head-on. Download this article to learn more. Read More