Natural language generation (NLG), the process of generating text or narratives based on a set of data values, can reach a broader audience. NLG narratives can be used for a variety of purposes, but in this perspective I focus on how NLG can be used to enhance business intelligence (BI) processes. In the case of BI, NLG can be used to explain what has happened and why it is happening, and even what actions to take. The NLG narratives can be understood by a broader range of business users than the tables and charts of data that are the typical output of most BI applications or analytics tools.
Longview recently completed the acquisition of Tidemark Systems, a planning software vendor. Longview Plan powered by Tidemark is a suite of cloud-based applications that enable corporations to plan, assess performance and communicate results more effectively. The software facilitates what Ventana Research calls “continuous planning.” This is a highly collaborative, action-oriented approach to planning that relies on frequent, short cycles to rapidly create and update integrated company-wide operational and financial plans. This structural approach makes it easy for individual business functions to create their own plans while enabling headquarters to connect those plans to create a unified view. Viewed in the long term, this acquisition provides Longview with a platform that will enable it to apply its existing on-premises intellectual property to a broader suite of web-based performance management and tax applications.
Topics: Mobile, Office of Finance, Recurring Revenue, Continuous Planning, Analytics, Business Intelligence, Financial Performance Management, Price and Revenue Management, ERP and Continuous Accounting, Sales Planning and Analytics
This is my second analyst perspective based on our IoT Benchmark Research. In the first, I discussed the business focus of IoT applications and some of the challenges organizations are facing. Now I’ll share some of the findings about technologies used in IoT applications and the impact those technologies appear to have on the success of users’ projects.
If we look at the focus of technology vendors for analytics and business intelligence or business applications providers deploying these capabilities in the last five years, we see that they have elevated the importance on the value of visualization and dashboards. These promotions might be understandable, but will they make business and the people using them more intelligent?
Topics: Big Data, data science, Mobile, Machine Learning, Analytics, Business Intelligence, Cloud Computing, Collaboration, Information Optimization, digital technology, Machine Learning and Cognitive Computing
This year various types of organizations are embracing machine learning like it is going out of style – or maybe it would be better to say coming into style. And now with a little investigation on LinkedIn finds over half million professionals with machine learning in their job title. Machine learning is the application of specific data science algorithms that become more accurate as the system records more outcomes and processes more data. This improvement is referred to as “learning,” hence the name. There are good reasons machine learning is growing so rapidly, but there are pitfalls to avoid as well.