Fast, flexible finance analytics
Go from rows to results
Finance moves fast. It’s time to move beyond the spreadsheet to a flexible business intelligence solution as sophisticated as your data. Discover what happens to your bottom line when you can see and understand your financial data.
In this short webinar series, we look at some of the challenges across multiple departments and demonstrate how intuitive, interactive visual analytics drive decisions that deliver better results across your organization.
To learn more about finance analytics, visit our Finance Analytics solutions page.
To see last year's finance analytics webinars, visit our Fundamentals of Finance Analytics webinar page.
How to analyze investment risk
Gaining a deeper insight into your investment portfolio can be a challenge. It requires investors seeking to understand the status of their positions to log into multiple portals, download spreadsheets, trim data, and combine them together. It’s a process that can take hours or even days a month. And as each second goes by, the data gets older and older--by the time you get your answers, the data is already out of date.
Driving proactive pricing analytics for FP&A
The finance departments of the future must be proactive rather than reactive. As companies adopt new business models like multi-tiered subscriptions, financial planning and analysis models become increasingly complex. Analysis during business model transitions is particularly complicated because traditional revenue streams remain important sources of revenue while new initiatives begin to take hold.
Advance your procurement performance with analytics
World class procurement organizations are increasingly leveraging data analytics tools and dashboards to uncover insights, opportunities, and accelerate value. These insights are often the basis for developing robust strategies that align with business stakeholders and help them in achieving their goals and objectives.
Tips to prep and validate your finance data
Financial data is messy. Traditional methods for preparing and transforming financial data for analysis are highly manual and time-consuming. With the extensive cleaning, enrichment, and shaping that happens with financial data, how do you build trust and confidence in your data once it’s been exported out of your source systems?