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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.
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 data warehouse architecture bi

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.

Compare Now

Business Intelligence (BI)

Business intelligence (BI) and performance management applications enable real-time, interactive access, analysis, and manipulation of mission-critical corporate information. These applications provide users with valuable insights into key operating information to quickly identify business problems and opportunities. Users are able to access and leverage vast amounts of information to analyze relationships and understand trends that ultimately support business decisions. These tools prevent the potential loss of knowledge within the enterprise that results from massive information accumulation that is not readily accessible or in a usable form. It is an umbrella term that ties together other closely related data disciplines including data mining, statistical analysis, forecasting, and decision support. 

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Documents related to » data warehouse architecture bi

The Data Warehouse Institute (TDWI) Conference in San Diego: The Agile Approach to Business Intelligence (BI)


Next month a TDWI World Conference will be taking place in San Diego, California. What’s so special about this conference anyway? The answer is simple:  the general topic is going to be “Creating an Agile BI Environment”. Progressively in the last four or five years, the agile software development methodology has been jumping from the software development area to the data warehouse

data warehouse architecture bi  Data Warehouse Institute (TDWI) Conference in San Diego: The Agile Approach to Business Intelligence (BI) Next month a TDWI World Conference will be taking place in San Diego, California. What’s so special about this conference anyway? The answer is simple:  the general topic is going to be “Creating an Agile BI Environment”. Progressively in the last four or five years, the agile software development methodology has been jumping from the software development area to the data warehouse space, as Read More

The Evolution of a Real-time Data Warehouse


Real-time data warehouses are common in some organizations. This article reviews the basic concepts of a real-time data warehouse and it will help you determine if your organization needs this type of IT solution.

data warehouse architecture bi  Evolution of a Real-time Data Warehouse The Evolution of a Real-time Data Warehouse Jorge Garcia - December 23, 2009 Understanding Real-time Systems Today, real time computing is everywhere, from customer information control systems (CICSs) to real-time data warehouse systems. Real-time systems have the ability to respond to user actions in a very short period of time. This computing behavior gives real-time systems special features such as instant interaction: users request information from the system Read More

Ask the Experts Question: Do Organizations Really Need a Physical Data Warehouse Structure?


We recently had a question from one of our readers (through our Ask the Experts page) discussing QlikView’s approach to data collection. Reader’s Question “QlikView says its innovative way of collecting data and not needing a physical data warehouse (DW) structure is the right thing to do in DW/business intelligence (BI) solutions. Can one expect to build a sustainable / scalable corporate

data warehouse architecture bi  Really Need a Physical Data Warehouse Structure? We recently had a question from one of our readers (through our Ask the Experts page) discussing QlikView’s approach to data collection. Reader’s Question “QlikView says its innovative way of collecting data and not needing a physical data warehouse (DW) structure is the right thing to do in DW/business intelligence (BI) solutions. Can one expect to build a sustainable / scalable corporate data warehouse through such an approach?” TEC Analyst Read More

SAS/Warehouse 2.0 Goes Live


SAS Institute has announced the production availability of SAS/Warehouse Administrator software, Version 2.0. This new version provides IT the ability to proactively publish data warehouse information and track its usage, plus aggressively manage the process of change in the data warehouse.

data warehouse architecture bi  ability to proactively publish data warehouse information and track its usage, plus aggressively manage the process of change in the data warehouse. Data warehouses and data marts have become a vital component of all successful data mining, knowledge management, business portal, e-intelligence, customer relationship management (CRM) and supplier relationship management (SRM) applications today, said Frank Nauta, product manager for SAS/Warehouse Administrator at SAS Institute. Nauta added, Successful Read More

Distilling Data: The Importance of Data Quality in Business Intelligence


As an enterprise’s data grows in volume and complexity, a comprehensive data quality strategy is imperative to providing a reliable business intelligence environment. This article looks at issues in data quality and how they can be addressed.

data warehouse architecture bi  opportunities. Even with a data warehouse that is well designed and equipped with the best tools for business intelligence (BI), users will encounter inefficiency and frustration if the quality of data is compromised. When embarking on a data warehousing or business intelligence project, it is essential for organizations to emphasize the quality of data that is used for analysis and subsequent decision making. As data captured from a multitude of sources makes its way to an enterprise data warehouse or Read More

Agile Data Masking: Critical to Data Loss Prevention and Threat Reduction


Over the past several years data loss and data leaks have been a regular part of headline news. This surge in data leak activity has prompted many organizations to reevaluate their exposure to data leaks and institute automated, agile approaches to data masking. Well-implemented data masking secures data delivery and enhances compliance and security while accelerating data management processes.

data warehouse architecture bi  Data Masking: Critical to Data Loss Prevention and Threat Reduction Over the past several years data loss and data leaks have been a regular part of headline news. This surge in data leak activity has prompted many organizations to reevaluate their exposure to data leaks and institute automated, agile approaches to data masking. Well-implemented data masking secures data delivery and enhances compliance and security while accelerating data management processes. Read More

Comparing Solace’s Broker-Based Architecture with Peer-to-Peer Architecture


When considering messaging middleware technologies, it’s important to understand the business requirements of a given application and consider them in context of the characteristics and strengths of the technology’s underlying architecture. This paper compares peer-to-peer messaging architecture with broker based architecture, and in particular Solace’s hardware-based appliance solution. Download the white paper and get the details.

data warehouse architecture bi  messaging middleware technology,peer-to-peer messaging architecture,Solaca''s broker-based architecture,messaging middleware,critical messaging characteristics,Solace Systems,Application system scalability,application system simplicity Read More

Considerations for Owning versus Outsourcing Data Center Physical Infrastructure


When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life expectancy, regulatory requirements, and other strategic factors. This paper discusses how to assess these key factors to help make a sound decision.

data warehouse architecture bi  for Owning versus Outsourcing Data Center Physical Infrastructure When faced with the decision of upgrading an existing data center, building new, or leasing space in a retail colocation data center, there are both quantitative and qualitative differences to consider. The 10-year TCO may favor upgrading or building over outsourcing; however, this paper demonstrates that the economics may be overwhelmed by a business’ sensitivity to cash flow, cash crossover point, deployment timeframe, data center life Read More

Logs: Data Warehouse Style


Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency.

data warehouse architecture bi  Data Warehouse Style Once a revolutionary concept, data warehouses are now the status quo—enabling IT professionals to manage and report on data originating from diverse sources. But where does log data fit in? Historically, log data was reported on through slow legacy applications. But with today’s log data warehouse solutions, data is centralized, allowing users to analyze and report on it with unparalleled speed and efficiency. Read More

Big Data Comes of Age: Shifting to a Real-time Data Platform


New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a unified view of the data terrain necessary to support big data and the real-time needs of innovative companies.

data warehouse architecture bi  Data Comes of Age: Shifting to a Real-time Data Platform New data sources are fueling innovation while stretching the limitations of traditional data management strategies and structures. Data warehouses are giving way to purpose-built platforms more capable of meeting the real-time needs of more demanding end users and the opportunities presented by big data. Read this white paper to learn more about the significant strategy shifts underway to transform traditional data ecosystems by creating a Read More

Data Blending for Dummies


Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant.

Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data providers, department data stores, in-house databases, and more, and become faster at delivering better information and results to their organizations. In the past, the challenge for data analysts has been accessing this data and cleansing and preparing the data for analysis. The access, cleansing, and preparing data stages are complex and time intensive. These days, however, software tools can help reduce the burden of data preparation, and turn data blending into an asset.

Read this e-book to understand why data blending is important, and learn how combining data means that you can get answers to your business questions and better meet your business needs. Also learn how to identify what features to look for in data blending software solutions, and how to successfully deploy these tools within your business. Data Blending for Dummies breaks the subject down into digestible sections, from understanding data blending to using data blending in the real world. Read on to discover how data blending can help your organization use its data sources to the utmost.

data warehouse architecture bi  Blending for Dummies Data analysts support their organization’s decision makers by providing timely key information and answers to key business questions. Data analysts strive to use the best and most complete information possible, but as data increases over time, so does the time required to identify and combine all data sources that might be relevant. Data blending allows data analysts a way to access data from all data sources, including big data, the cloud, social media sources, third-party data Read More

Implementing Energy-Efficient Data Centers


But in the white paper implementing energy-efficient data centers, you'll learn how to save money by using less electricitywhether your data cente...

data warehouse architecture bi  Energy-Efficient Data Centers Did you realize that your data center(s) may be costing you money by wasting electricity ? Or that there are at least 10 different strategies you can employ to dramatically cut data center energy consumption ? The fact is, most data centers are not designed with energy efficiency in mind. But in the white paper Implementing Energy-efficient Data Centers , you''ll learn how to save money by using less electricity—whether your data centers are still in the design Read More

Increasing Sales and Reducing Costs across the Supply Chain-Focusing on Data Quality and Master Data Management


Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset.

data warehouse architecture bi  the Supply Chain-Focusing on Data Quality and Master Data Management Nearly half of all US companies have serious data quality issues. The problem is that most are not thinking about their business data as being valuable. But in reality data has become—in some cases—just as valuable as inventory. The solution to most organizational data challenges today is to combine a strong data quality program with a master data management (MDM) program, helping businesses leverage data as an asset. Read More

Architecture-Centered Information Systems In The Manufacturing Domain - Part II - The Architecture Process


Architecture bridges the semantic gap between the requirements and software. Application software systems must be architected in order to deal with the current and future needs of the business organization. Managing software projects using architecture-centered methodologies must be an intentional step in the process of deploying information systems — not an accidental by-product of the software acquisition and integration process.

data warehouse architecture bi  used to separate the data from the applications. Legacy applications hold information within their boundaries that must be integrated with the new system. In many instances, it is not feasible to move this legacy data to a new system. Workflow engines used to manage the business processes. In many environments the work processes are fluid, changing with the business climate. Adapting the work processes to the business process is usually done through some form of workflow. Using this context, the Read More

Architecture-Centered Information Systems In The Manufacturing Domain - Part III - Steps in the Architecture Process


Architecture bridges the semantic gap between the requirements and software. Application software systems must be architected in order to deal with the current and future needs of the business organization. Managing software projects using architecture–centered methodologies must be an intentional step in the process of deploying information systems – not an accidental by–product of the software acquisition and integration process.

data warehouse architecture bi  identifies and specifies the data and processes of the system in an informal manner [Bell98]. The CRC Card method is based on the theory of role-playing in which the participants have specific knowledge about their own roles and make requests of other participants to gain knowledge of their roles. Through this role-playing the nouns and verbs of the system are revealed. 4+1 and UML If the UML is to be used in the development of the system architecture described in 4+1, then the different components of Read More