• Business Analytics for the Finance Sector

    In today’s post financial crisis environment, banks face a costly and complex web of challenges that have become their new normal. Customers are now more savvy, demanding and less loyal. New regulations continue to emerge that require more granular and frequent demonstrations of governance and control. The ability to understand risk well enough to act on insights remains a challenge. And capital remains scarce, requiring a tighter focus on operational efficiency and decisions that are both risk-informed and capital adjusted. The competition for profitable returns in this marketplace is extreme. In order to meet the challenges of the “new normal,” banks need a way to transform massive volumes of organizational data into actionable insights and strategies – Business analytics is the perfect tool.

  • The Economy of Things

    Thanks to the Internet of Things (IoT), physical assets are turning into participants in real-time global digital markets. The countless types of assets around us will become as easily indexed, searched and traded as any online commodity. While some industries will be tougher to transform than others, untold economic opportunities exist for growth and advancement, creating a new “Economy of Things” with significant consequences. That won’t just mean smart homes that light up when you arrive or washing machines that text you when the cycle is done…

  • Big data, bad data, good data – The link between information governance and big data outcomes

    The outcome of any big data analytics project is only as good as the quality of the data being used. As big data analytics solutions have matured, the quality and trustworthiness of the data sources themselves are emerging as key concerns. Although organizations may have their structured data under control, this is often not the case with the unstructured content that accounts for the vast majority of enterprise information. This paper explores the link between good information governance and the outcomes of big data analytics projects and takes a look at IBM’s StoredIQ solution.

  • IBM BI Forward – a full view of your business

    Imagine that your organization is effectively using a business intelligence (BI) solution that provides everything you need to make better decisions and improve operational efficiency. Imagine users with their fingers on the pulse of markets, customers, channels and operations at all times. And imagine that your programs, plans, services and products are being designed with full and timely insight into all the factors — past, present and future — critical to success. What would it take to make that happen?

  • Business Analytics for Big Data

    Organisations today collect more data than ever before. Much of it is difficult to analyze, yet the insights contained in this data can be extremely valuable. New technologies for managing, exploring and analyzing data have advanced so far that it is now feasible for organizations of all sizes to capitalise on big data.

  • Better Planning and Forecasting with Predictive Analytics and TM1

    If you look up “forecast” and “predict” in the dictionary, you’ll find that the two words mean roughly the same thing. But until now, those involved in financial forecasting have not been able to take advantage of the latest advances in predictive analytics software.