Group items tagged

For the fourth consecutive year, Gartner, Inc. has named Oracle as a Leader in its “Magic Quadrant for Master Data Management of Product Data Solutions.” (1)

“MDM is a technology-enabled discipline in which business and IT staff work together to ensure the uniformity, accuracy, stewardship, semantic consistency and accountability of the enterprise's official, shared master data assets. Master data is the consistent and uniform set of identifiers and extended attributes that describes the core entities of the enterprise, such as customers, prospects, citizens, suppliers, sites, hierarchies and chart of accounts,” according to Gartner.

By enabling organizations to consolidate product information from heterogeneous systems, Oracle Product Hub creates a single view of product information that can be leveraged and shared across functional departments in the enterprise, as well as externally with trading partners.

Pentaho, for instance, is one of this year’s rookies. It had been knocking on the door for a year or two and received an honorable mention last year. It needed to increase its overall sales figures to be cited by Gartner, a requirement it satisfied this year.

Big Data is forecast to drive $34 billion of IT spending in 2013 and create 4.4 million IT jobs by 2015, but it is currently still a solution looking for a problem, according to analyst firm Gartner.

While businesses are keen to start mining their data stores for useful insights, and many are already experimenting with technologies like Hadoop, the biggest challenge is working out what question you are trying to answer

Integration BI infrastructure: All tools in the platform use the same security, metadata, administration, portal integration, object model and query engine, and should share the same look and feel. Metadata management: Tools should leverage the same metadata, and the tools should provide a robust way to search, capture, store, reuse and publish metadata objects, such as dimensions, hierarchies, measures, performance metrics and report layout objects. Development tools: The platform should provide a set of programmatic and visual tools, coupled with a software developer's kit for creating analytic applications, integrating them into a business process, and/or embedding them in another application. Collaboration: Enables users to share and discuss information and analytic content, and/or to manage hierarchies and metrics via discussion threads, chat and annotations.

Information Delivery Reporting: Provides the ability to create formatted and interactive reports, with or without parameters, with highly scalable distribution and scheduling capabilities. Dashboards: Includes the ability to publish Web-based or mobile reports with intuitive interactive displays that indicate the state of a performance metric compared with a goal or target value. Increasingly, dashboards are used to disseminate real-time data from operational applications, or in conjunction with a complex-event processing engine. Ad hoc query: Enables users to ask their own questions of the data, without relying on IT to create a report. In particular, the tools must have a robust semantic layer to enable users to navigate available data sources. Microsoft Office integration: Sometimes, Microsoft Office (particularly Excel) acts as the reporting or analytics client. In these cases, it is vital that the tool provides integration with Microsoft Office, including support for document and presentation formats, formulas, data "refreshes" and pivot tables. Advanced integration includes cell locking and write-back. Search-based BI: Applies a search index to structured and unstructured data sources and maps them into a classification structure of dimensions and measures that users can easily navigate and explore using a search interface. Mobile BI: Enables organizations to deliver analytic content to mobile devices in a publishing and/or interactive mode, and takes advantage of the mobile client's location awareness.

Analysis Online analytical processing (OLAP): Enables users to analyze data with fast query and calculation performance, enabling a style of analysis known as "slicing and dicing." Users are able to navigate multidimensional drill paths. They also have the ability to write back values to a proprietary database for planning and "what if" modeling purposes. This capability could span a variety of data architectures (such as relational or multidimensional) and storage architectures (such as disk-based or in-memory). Interactive visualization: Gives users the ability to display numerous aspects of the data more efficiently by using interactive pictures and charts, instead of rows and columns. Predictive modeling and data mining: Enables organizations to classify categorical variables, and to estimate continuous variables using mathematical algorithms. Scorecards: These take the metrics displayed in a dashboard a step further by applying them to a strategy map that aligns key performance indicators (KPIs) with a strategic objective. Prescriptive modeling, simulation and optimization: Supports decision making by enabling organizations to select the correct value of a variable based on a set of constraints for deterministic processes, and by modeling outcomes for stochastic processes.

Gartner defines advanced analytics as, "the analysis of all kinds of data using sophisticated quantitative methods (for example, statistics, descriptive and predictive data mining, simulation and optimization) to produce insights that traditional approaches to business intelligence (BI) — such as query and reporting — are unlikely to discover."

packaged analytics applications that target specific business domains

Revolution Analytics

Add in the easy-to-use nature of social networks, and the potential value of CRM accelerates even faster. The Social Enterprise as defined by Salesforce.com, heavily promoted at their DreamForce event last month in San Francisco, capitalizes on these factors which are critical for any CRM system to succeed.

Add in the easy-to-use nature of social networks, and the potential value of CRM accelerates even faster. The Social Enterprise as defined by Salesforce.com, heavily promoted at their DreamForce event last month in San Francisco, capitalizes on these factors which are critical for any CRM system to succeed.

relational database management systems (DBMSs) used as platforms for data warehouses

It is important to note that a DBMS does not in itself constitute a data warehouse — rather, a data warehouse can be deployed on a DBMS platform.

a data warehouse is simply a warehouse of data, not a specific class or type of technology

Web registration pages and campaigns, direct mail campaigns, email marketing, multichannel campaigns, database marketing and third-party leased lists, social CRM and social networking sites, and tradeshows.

SugarCRM

Chatter and Data.com