Predictive models and analysis are typically used to forecast future probabilities. Applied to business, predictive models are used to analyze current data and historical facts in order to better understand customers, products and partners and to identify potential risks and opportunities for a company. It uses a number of techniques, including data mining, statistical modeling and machine learning to help analysts make future business forecasts.
Oracle and Microsoft are among the vendors of business intelligence dashboards. BI dashboards can also be created through other business applications, such as Excel. Business intelligence dashboards are sometimes referred to as enterprise dashboards.
The business intelligence dashboard is often confused with the performance scorecard. The main difference between the two, traditionally, is that a business intelligence dashboard, like the dashboard of a car, indicates the status at a specific point in time. A scorecard, on the other hand, displays progress over time towards specific goals. Dashboard and scorecard designs are increasingly converging. For example, some commercial dashboard products also include the ability to track progress towards a goal. A product combining elements of both dashboards and scorecards is sometimes referred to as a scoreboard.
Quantifying your compliance with all vendors, license agreements, leases, warranties, & contracts no matter how complex, yielding the following results:
Reducing labor costs expended in the investigation & resolution of compliance conflicts.
Optimizing management of multiple types of contracts for hardware or software assets.
Accurately discovering & reporting real time usage of software suites via local, remote, or mobile sources, yielding the following results:
Reducing contract costs expended on unused, underutilized, or under-deployed or over-deployed software.
- Increasing current contract value with recommended license upgrade, conversion, consolidation or elimination
Data integration is best performed within a data warehouse (DW). A DW enables employees of an organization to perform analyses on all the data flowing into the DW regardless of its source. BIQed can assist your organization in identifying disparate sources of data where crucial data is currently stored, and create a strategic roadmap to design, implement, integrate, test and migrate the data into a data warehouse solution.
Imagine trying to build a house without a blueprint. Sounds crazy, but that’s essentially what data management pros are doing if they neglect data modeling concepts before embarking on master data management (MDM) or business intelligence (BI) initiatives.
A data model, explains Steve Hoberman, author of a recent book on the topic called <i>Data Modeling for the Business</i>, is essentially the underlying architectural diagram that guides any number of data management and other IT projects, from MDM and BI to application development. He explains that data models come in different varieties and play different roles, depending on the particular project. To get a basic understanding of how data modeling works and how to use it to its fullest advantage, follow the links below.
There are a variety of ERP applications which automate and support a range of administrative and operational business processes across multiple industries, including line of business, customer-facing, administrative and the asset management aspects of an enterprise. Thus, it touches the same areas as business intelligence while focusing on a different end goal.
- Are there IT cost savings to be discovered or utilized?
- Can my current business process be increased in efficiency?
- Can I standardize my current business processes?
- How will ERP become a catalyst for business innovation.