La version 15.3 de CA Project & Portfolio Management (CA PPM) vous permet de personnaliser les projets pour chaque business unit par de simples opérations de glisser-déposer. Qu’il s’agisse de workflows complexes pour les ressources humaines ou de simples tâches de gestion des ventes, les projets peuvent désormais être lancés en quelques minutes, au lieu de plusieurs jours.
Ajoutez à cela des possibilités de collaboration au départ de l’application proprement dite pour éliminer les réunions superflues, un format de tableau familier de type Microsoft Excel® pour gérer les budgets, de nouvelles connexions à des outils d’aide à la décision tiers pour trouver des réponses, et vous obtenez l’application de gestion de portefeuilles de projets la plus moderne du marché.
Published By: Tableau
Published Date: Apr 13, 2018
In this whitepaper, discover the benefits of expanding your analytics toolkit. Combine Excel’s data collection and management capabilities with Tableau’s intuitive, analytical power to transform your raw data into actionable insights. Focus on the questions that take your data beyond the spreadsheet.
Read more at about this partnership.
Financial institutions run on data: collecting it, analyzing it, delivering meaningful insights, and taking action in real time. As data volumes increase, organizations demand a scalable analytics platform that can meet the needs of data scientists and business users alike. However, managing an on-premises analytics environment for a large and diverse user base can become time-consuming, costly, and unwieldy.
Tableau Server on Amazon Web Services (AWS) is helping major Financial Services organizations shift data visualization and analytics workloads to the cloud. The result is fewer hours spent on manual work and more time to ask deeper questions and launch new data analyses, with easily-scalable support for large numbers of users. In this webinar, you’ll hear how one major asset management company made the shift to cloud data visualization with Tableau Server on AWS. Discover lessons learned, best practices tailored to Financial Services organizations, and starting tactics for scalable analytics on the cloud.
Self-service analytics implies that users design and develop their own reports and do their own data analysis with minimal support by IT. Most recently, due to the availability of tools, such as those from Qlik, Spotfire, and Tableau, self-service analytics has become immensely popular. Besides powerful analytical and visualization capabilities, they all support functionality for accessing and integrating data sources. With respect to this aspect of data integration four phases can be identified in the relatively short history of self-service analytics. This whitepaper describes these four phases in detail and shows how the tools Cisco Data Preparation (CDP) and Cisco Information Server (CIS) for data virtualization can strengthen and enrich the self-service data integration capabilities of tools for reporting and analytics.
A new generation of business intelligence emerges as the expectation for user-friendly analytics and the expertise to ask and answer questions with data continues to grow. The wave of innovation is far from over. This paper highlights the top trends in business intelligence for 2015.
Get started by creating the best type of chart for your data and questions. From there, you’ll quickly find you’re not only answering your initial questions, but telling amazing stories with your data.
Congratulations: you are part of a small but growing group that’s taking advantage of the power of visualization. However, bringing your visualizations from “good” to “great” takes time, patience, attention to detail, and some basic knowledge of visual analysis best practices.
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