analytic model

Survey closes this week – Predictive Analytics in the Cloud

This is the last week for our 2013 survey on Predictive Analytics in the Cloud – Use Cases, Trends and Big Data.  Please go right now and take the survey here – it’s quick , anonymous and you have a chance to win a $100 Amazon gift card. There’s been tremendous growth cloud and predictive analytics both […]

Predictive Analytics in Software Part 4: Land and Expand

Most software products have multiple opportunities for using predictive analytics to enhance decision-making. Because the use of predictive analytics is new for many software companies, and because handling decisions explicitly is also new, care must be taken not to bite off too much at once. A land and expand strategy that begins with a localized […]

Predictive Analytics in Software Part 3: Automation that Scales

For a software company it is also important that this automation scales appropriately. In particular any automated analytic model development tool you use should provide flexibility in deployment to match your own, manage any variability between your customers’ data models and be easy to deploy, focused on the “last mile” of analytic model development. For most […]

Predictive Analytics in Software Step 2: Focusing on Automation

Once you have identified decisions that could usefully be improved by predictive analytics you must develop predictive analytic models for each decision. Each decision is going to require a different predictive analytic model, perhaps several. Some predictive analytic models, such as predicting the future value of a customer for instance, may be useful in multiple […]

A Practitioner Speaks: Requirements for analytic projects

Continuing to expand on the questions I asked Andrea Scarso co-founder and COO of MoneyFarm when I interviewed him I wanted to focus on the question “How, specifically, do you develop requirements for analytic projects?” “In my opinion, it is paramount to start from the single and specific decision needed. Then, with a top-down process, to analyze its component elements: hard data, […]

A Practitioner Speaks: Top challenges for analytic professionals

One of the questions I asked Andrea Scarso co-founder and COO of MoneyFarm when I interviewed him was “In your experience what are some of the top challenges for analytic professionals in terms of maximizing the business impact of what they do?” In this post I’ll take a couple of his comments and expand on them […]

A Practitioner Speaks: Analytics and Decision Management

I recently caught up with Andrea Scarso, co-founder and COO of MoneyFarm. MoneyFarm is a startup whose target is to modernize and democratize the European panorama of retail investment services, leveraging the opportunities offered by the web and by process automation. Andrea designed the main decisioning processes. What’s your background, how did you come to be working in analytics? […]

Big Data and Decision Management Systems: The impact of Velocity

The third and final post in my series on the impact of Big Data on Decision Management Systems: The impact of Velocity. As more data arrives more quickly we have to deal with velocity in two ways – we have to decide more quickly and we have to deal with data “in motion” – streaming […]

Big Data and Decision Management Systems: The impact of Variety

The second in my series on the impact of Big Data on Decision Management Systems: The impact of Variety. Big Data involves adding more types of data, from more sources inside and outside of the organization, to your analytic toolkit. Social, mobile, local and cloud data sources are exploding and organization must find ways to […]

Big Data and Decision Management Systems: The impact of Volume

Big Data is often described in terms of an increase in volume, an increase in velocity and an increase in variety: More data, of more types, arriving more quickly. In this short series of blog posts I will discuss the impact of each aspect of Big Data on Decision Management Systems – systems designed to […]