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Software Functionality Revealed in Detail
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 perspectives on data warehousing 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) RFI / RFP Template

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

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Business Intelligence: A Guide for Midsize Companies


Business intelligence (BI) is not a new concept. What’s new is that BI tools are now accessible for midsize companies. Managers can use BI to analyze complex information to support their decision-making processes, combining data from a variety of sources to get an integrated, 360-degree view of the company. Find out how to select the right BI software, the right vendor, and the right approach to implementing BI.

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Contemporary Business Intelligence and Its Main Components


Business intelligence (BI) represents the tools and systems that play a key role in the strategic planning process by allowing a company to manipulate corporate data for decision-making. But what exactly are the primary components of BI?

perspectives on data warehousing bi  and innovation and learning perspectives that formally connect overall objectives, strategies, and measurements (since each dimension may have goals and measurements). To make a clear difference between dashboards and scorecards (the terms are often confused or used interchangeably), a dashboard is a digital cockpit that produces a snapshot of a moment in time, which can be drilled through. Scorecarding is the process of comparing actual results to target results, and of discerning trends over a period Read More

Creating Competitive Advantage in Growing and Mid-sized Businesses with Business Intelligence


Business intelligence (BI) is not only an imperative for big companies. Growing and midsized organizations also require visibility into all aspects of the business for their day-to-day decision-making, with accurate, reliable, and up-to-date information. We outline the issues, business ramifications, and solutions for the BI requirements of growing companies.

perspectives on data warehousing bi  | SAP Business Intelligence Perspectives | SAP Business Intelligence Overview | SAP Business Intelligence 2.0 | SAP Enterprise Business Intelligence | SAP Technology Business Intelligence | SAP Active Business Intelligence | SAP Business Analysis Tools | SAP Business Intelligence Field | SAP Business Intelligence Source | Business Analytics SAP | Business Intelligence SAP | Business Intelligence Advisors SAP | Business Intelligence Analytics SAP | Business Intelligence Application SAP | Business Read More

Unlocking Hidden Value from Investments in SAP NetWeaver Business Warehouse


Extending the capabilities and value of SAP NetWeaver Business Warehouse is a concern for users. To improve data use and fact-based decision making, and reduce stranded spreadsheets, SAP users can choose a business intelligence (BI) software solution such as IBM Cognos 8, with budgeting, planning, and forecasting functions. Find out more about how you can improve your business performance management content with BI.

perspectives on data warehousing bi  reports lacking context and/or perspectives on information become the norm. Although the intent of generating data to drive decisions is noble, the common result is a decentralized and ungoverned data reporting and analysis approach. In addition, the value of data is degraded, excessive amounts of time is spent reconciling and rationalizing multiple data points, view points and perspectives. As overlapping and uncontrolled reports, spreadsheets and custom applications are developed to fill a perceived Read More

Business Intelligence Status Report


Spurred by government mandates for more business transparency, business intelligence has emerged to extract information from ERP systems. How has BI emerged? What does the terminology surrounding it mean, and what is its current state of affairs?

perspectives on data warehousing bi  business information from multiple perspectives. Users are able to perform multi-dimensional analysis, slice-and-dice data sets, and drill-down to additional detail, all using integrated OLAP technology, whose analytical functionality should ideally be available whether users are connected to the Internet, through a mobile, or are working off-line. Data warehousing also led to the development of the concept of metadata management, whereby metadata is data about data, such as table and column names, and Read More

2011 Business Intelligence Buyer's Guide: BI for Everyone


This buyer guide is for business owners, managers, decision makers, and anyone interested in learning about the deployment of business intelligence (BI) systems across large enterprises as well as small to medium businesses (SMBs). It presents a comprehensive view of the wide spectrum of BI software solutions currently available and investigates how they match different types of organizations according to size and need.

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Data Quality: A Survival Guide for Marketing


Even with the finest marketing organizations, the success of marketing comes down to the data. Ensuring data quality can be a significant challenge, particularly when you have thousands or even millions of prospect records in your CRM system and you are trying to target the right prospect. Data quality, data integration, and other functions of enterprise information management (EIM) are crucial to this endeavor. Read more.

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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.

perspectives on data warehousing bi  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 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.

perspectives on data warehousing 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

A Solution to Data Capture and Data Processing Challenges


Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems.

perspectives on data warehousing bi  Solution to Data Capture and Data Processing Challenges Organizations are relying more and more on customer information to drive business processes. You probably spend a lot of time trying to make sure you get the right information to the right people at the right time—but is your data capture process as efficient as it could be? Learn about the issues surrounding data capture and data processing, and about a solution designed to help you address specific processing problems. Read More

10 Errors to Avoid When Building a Data Center


In the white paper ten errors to avoid when commissioning a data center, find out which mistakes to avoid when you're going through the data center...

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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.

perspectives on data warehousing bi  Data Management,Data Infrastructure,Data Center,Knowledge Management,Cost Control,IT Budgeting,Outsourcing,Strategic Planning,Business Applications,Business Management,data management software,data management technology,enterprise data management,data management services,customer data management 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...

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