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Software Functionality Revealed in Detail
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 data visualization


Data Visualization: When Data Speaks Business
For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is

data visualization  Business For many organizations, data visualization is a practice that involves not only specific tools but also key techniques, procedures, and rules. The objective is to ensure the best use of existing tools for extending discovery, gaining knowledge, and improving the decision-making process at all organizational levels. This report considers the important effects of having good data visualization practices and analyzes some of the features, functions, and advantages of IBM Cognos Business Intelligence

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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.

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 Performance Management (BPM) RFI/RFP Template

Data Visualization, Analytics, Workflow, Data Integration, Support, System Requirements 

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Documents related to » data visualization

Making Big Data Actionable: How Data Visualization and Other Tools Change the Game


To make big data actionable and profitable, firms must find ways to leverage their data. One option is to adopt powerful visualization tools. Through visualization, organizations can find and communicate new insights more easily. Learn how to make big data more actionable by using compelling data visualization tools and techniques.

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Kronos Simplifies Workforce Big Data with Self-service Visualization


One of the major announcements at the KronosWorks 2013 conference was about the transformative change coming to Kronos Workforce Analytics at the end of 2013. By leveraging Microstrategy Visual Insight, Kronos intends to put the power of workforce data analytics into the hands of the managers who can immediately act on it by leveraging data visualization and exploration tools. The introduction

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Picture This: Self-service BI through Data Discovery and Visualization


Organizations are finding it increasingly difficult to get the right information to the right people at the right time, and business managers are facing a shrinking “decision window.” With many companies also dealing with increasing volumes of data, this gives rise to an opportunity for innovation in analytics. This article uses the results of an agile business intelligence (BI) survey to examine the performance of organization that provide business users with visual tools that let them freely and easily explore data to discover new insights.

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A Simplified Approach to Powerful, Flexible Data Visualization


Corda's CenterView™ enterprise performance dashboards allow users and software partners to use Corda's dashboards to create the presentation layer of analytics, and to help organizations present and achieve their business goals across the organization.

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Unified Data Management: A Collaboration of Data Disciplines and Business Strategies


In most organizations today, data are managed in isolated silos by independent teams using various data management tools for data quality, integration, governance, and so on. In response to this situation, some organizations are adopting unified data management (UDM), a practice that holistically coordinates teams and integrates tools. This report can help your organization plan and execute effective UDM efforts.

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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.

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Customer Data Integration: A Primer


Customer data integration (CDI) involves consolidation of customer information for a centralized view of the customer experience. Implementing CDI within a customer relationship management initiative can help provide organizations with a successful framework to manage data on a continuous basis.

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Data Integration: Creating a Trustworthy Data Foundation for Business Intelligence


Organizations combine their historical data with current data from operational systems to satisfy business intelligence analysis and government reporting requirements. This paper discusses the importance of data integration and helps you identify key challenges of integrating data. It also provides an overview of data warehousing and its variations, as well as summarizes the benefits and approaches to integrating data.

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Metagenix Reverse Engineers Data Into Information


Metagenix’ MetaRecon reverse engineers metadata information by examining the raw data contained in the source(s) rather than depending on the data dictionaries of the existing legacy systems (which are often incorrect). Other unique Metagenix approaches include an "open book" policy, which includes publishing product price lists on their web site and complete access to company officials, including CEO and President Greg Leman. According to Mr. Leman, "we’re pathologically honest".

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Re-think Data Integration: Delivering Agile BI Systems with Data Virtualization


Read this white paper to learn about a lean form of on-demand data integration technology called data virtualization. Deploying data virtualization results in business intelligence (BI) systems with simpler and more agile architectures that can confront the new challenges much more easily.

All the key concepts of data virtualization are described, including logical tables, importing data sources, data security, caching, and query optimization. Examples are given of application areas of data virtualization for BI, such as virtual data marts, big data analytics, extended data warehouse, and offloading cold data.

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