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LIST REPORTING
LIST REPORTING
The most common usage of Enterprise Reporting is the formatted displays or presentations of organizational data lists through list, text, graphics or other rendering formats for periodic business operation. Various levels of itemized rows and aggregated summaries are typically used in List Reporting. Data rows and summaries might be assembled from one or more than one functional discipline areas within the enterprises.
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INTERACTIVE ANALYSIS
INTERACTIVE ANALYSIS
Enterprise users needs to perform analysis upon large set of data to understand or find presentation of the data. These analysis typically are interactive and allow users to directly select dimensions (location, department, time, etc) to compare measurements (sales growth, cost distributions, amount etc). The interactive analysis requires data readily available when different dimentions, measurement are chosen so typically data are pre-calculated or aggregated using specific data model like OLAP.
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AD-HOC QUERYING
AD-HOC QUERYING
Ability to allow advanced business users for ad-hoc data needs and play “what-if” scenarios to determine what are the best use of enterprise data. Most of time it involves Excel or other front-end easy tools for those users to analysis or querying data.
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METRIC / DASHBOARD
METRIC / DASHBOARD
In many organizations, business performance is managed and measured through outcome-oriented metrics. These metrics are agreed measurement to track and compare the business performance over a period of time. Within the organization, these are mostly called Key Performance Indicators (KPIs). For external organizations, they are Service Level Agreement (SLAs).
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BALANCE SCORECARDS
BALANCE SCORECARDS
Another way for enterprise to consume their reporting data is publishing them into customized dashboard views, mostly hosted within enterprises’ internet portal. These dashboards might use graphic to mimic color-coded auto dashboard indicator for easy but grand overview of enterprise’s key performance.
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DATA MINING
DATA MINING
When enterprise holds large amount of data, many of them started to analysis using Data Mining technique neural networks and machine learning to study and find potential common patterns in the data. Most of the data mining takes time and dimensions into account to try to predict or forecast the learning.