![]() ![]() ![]() collaborative BI (collaborative business intelligence)Ĭollaborative BI (collaborative business intelligence) is the merging of business intelligence software with collaboration tools, including social and Web 2.0 technologies, to support improved data-driven decision making.Cloud analytics applications and services are typically provided through a subscription-based or utility (pay-per-use) model. business intelligence competency center (BICC)Ī business intelligence competency center (BICC) is a team of people that, in its most fully realized form, is responsible for managing all aspects of an organization's BI strategy, projects and systems.Ī business intelligence dashboard, or BI dashboard, is a data visualization and analysis tool that displays on one screen the status of key performance indicators (KPIs) and other important business metrics and data points for an organization, department, team or process.Ĭampbell's Law is the observation that once a metric has been identified as a primary indicator for success, its ability to accurately measure success tends to be compromised.Ī citizen data scientist is any individual who contributes to the research of a complex data initiative but who does not have a formal educational background in data analytics (DA) or business intelligence (BI).Ĭloud analytics is a service model in which one or more key element of data analytics is provided through a public or private cloud.BIRT (Business Intelligence and Reporting Tools)īIRT (Business Intelligence and Reporting Tools) is an open source technology platform sponsored by the Eclipse Foundation that consists of a visual report designer and a runtime component for Java and Java EE environments.īusiness analytics (BA) is the iterative, methodical exploration of an organization's data, with an emphasis on statistical analysis.īusiness intelligence (BI) is a technology-driven process for analyzing data and delivering actionable information that helps executives, managers and workers make informed business decisions.Ī business intelligence architecture is the framework for the various technologies an organization deploys to run business intelligence and analytics applications.Second, the end-user can bring in his or her own data and combine it with those made available in the platform.Association rules are 'if-then' statements, that help to show the probability of relationships between data items, within large data sets in various types of databases.īig data analytics is the often complex process of examining big data to uncover information - such as hidden patterns, correlations, market trends and customer preferences - that can help organizations make informed business decisions. First, users can combine data fields from data sources that have been intentionally exposed to the BI platform but not yet mapped together in a data schema. Data mashup flexibility applies to two common use cases. It allows end-users to iteratively create and define data mashups on their own and immediately visualize and analyze the resulting data blocks. InetSoft’s BI platform for data mashup uniquely takes this data agility concept to the ultimate level by fusing data mashup with business analytic in one web app. But they can also introduce new data with mash up and bring self-service to a different level. Not only they can repurpose data like Lego blocks for unanticipated querstion. This is now being referred to as “data mashup.” While combining disparate data sources is a common application for a data mashup, note that even in a single data source environment a mashup can be made by combining data from different tables in a way that had not been previously anticipated.ĭata mashup empowers power-user, analyst, or business person who normally studies dashboards or sifts through reports with underlying data. Within the data analytics and BI industry, a small number of vendors have been creating applications that allow the combination or mashup of disparate data sources to be improvised without necessarily relying on a IT heavy step of ETL and data warehousing. ![]()
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