SuccessFactors Employee Central provides a single employee global system of record that is deployed in the cloud and brings greater workforce visibility to small and medium-size businesses. HR can quickly integrate workforce data from the SuccessFactors BizX Suite of talent management solutions – including Performance and Goals, Compensation, Learning and more, as well as from third-party systems, such as payroll, benefits, and time and attendance. Employees can use the Employee Central self-service features to update their personal information, while managers can easily change employee information such as promotions, salary changes, terminations and more with customized approval workflows. The result: An integrated 360-degree view of the workforce that HR can access through standard and ad-hoc reports to make fast, informed decisions based on consistent, up-to-date data. To learn more, download the SuccessFactors Employee Central business brief for small to medium-size businesses
Quest Workspacetm Help Desk is a robust help desk solution for small to medium-sized businesses with complex network environments. It provides a powerful combination of management features integrated with a best-of-breed IT help desk platform. Use the help desk software to manage the ticket system workflows, dashboards, reporting and end-user self-service portals. Use the embedded management features within the help desk platform to proactively manage network events, desktops, servers and applications as well as resolve issues faster and more effectively.
When designed well, a data lake is an effective data-driven design pattern for capturing a wide range of data types, both old and new, at large scale. By definition, a data lake is optimized for the quick ingestion of raw, detailed source data plus on-the-fly processing of such data for exploration, analytics and operations. Even so, traditional, latent data practices are possible, too.
Organizations are adopting the data lake design pattern (whether on Hadoop or a relational database) because lakes provision the kind of raw data that users need for data exploration and discovery-oriented forms of advanced analytics. A data lake can also be a consolidation point for both new and traditional data, thereby enabling analytics correlations across all data.
To help users prepare, this TDWI Best Practices Report defines data lake types, then discusses their emerging best practices, enabling technologies and real-world applications. The report’s survey quantifies user trends and readiness f
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