Guest post by Micro Focus IDOL General Manager, Ken Muir 

The terms “AI” and “Analytics” (or Artificial intelligence and Analytics) have become overused buzz-words without consistent definitions nor understand by many who use the term. Micro Focus has been a leader in “AI-powered Analytics” for over a decade well before the industry hype. Our approach is unique because we holistically address the need to analyze all forms of data regardless of the format and origin as indicated by a recent Forrester Wave: AI-Based Text Analytics Platforms. We define AI-powered analytics in four major categories; Product Improvement Monitoring, System Health & Performance, Operational Analytics and Advanced Analytics.  

Product Improvement Monitoring 

This is typically defined by metrics and data about how a particular product is being used and how the product is performing in its deployed environment. It is often associated with “Call home” features where end-users can opt-in whether or not they want to participate in this data collection. Ultimately this data enables product developers to create better products to better solve the problems customers have. 

System Health & Performance 

These are the metrics of how a particular product is performing in relation to the resources it requires to operate efficiently. Server load, Endpoint availability, disk space usage, memory/CPU consumption, etc. Additionally with today’s intelligent applications this data would include root-cause analysis of problems and action that the software took to correct the problem. This category of analytics is important to the end customer because it enables better performance and self-correction of their critical business workloads. 

Operational Analytics 

These types of analytics contain reporting specific to the solution and the business problem the solution solves. Administrators and LOB managers obtain insights into details such as what data-types are captured, backed-up, indexed, discovered, user counts, actions taken on data per policy, and other KPI type statistics. 

Advanced Analytics 

It could be said that the three previous categories are more traditional product data details that have been provided by well build software applications for years and not analytics in terms of what we call “Advanced Analytics”. This is where analytical software mines large data-sets produced by the product or usage of the product and automatically spots trends, patterns and abnormalities that enable the end user to understand what is going on and predict what will happen in the future. This machine learning of the data by advanced analytics platforms, such as Micro Focus IDOL is ultimately what most end-customers need in order to understand today’s massively large data-sets and leverage that data to drive the best possible business outcomes. 

Analytics in Micro Focus Products 

The first part of our company mission statement reads; “We provide our customers with a best-in-class portfolio of enterprise-grade scalable software with analytics built in.” Across all our products, customers will find one or more of the above categories of analytics implemented within the software that enable us to product the best software in the world and for our customers to maximize the performance and business outcomes derived from our software. We leverage our core analytics platforms in IDOL and Vertica on top of our other products, where it makes sense, to provide even deeper understanding of customer data as well and predicting future outcomes. 

The second part of our mission statement reads; “We put customers at the center of our innovation and build high quality products that our customers can rely on and our teams can be proud of.” Key to Micro Focus’ overall strategy is the delivery of what we call “customer centered innovation”. In essence we focus on innovation that delivers tangible business impact for customers. This can mean both through the enablement of new business models or use cases through to what I believe will be of most interest to customers, protecting existing investments and extending productive use of our products within our customer base. Our goal is to protect our customers investment in our products by helping them “bridge the old and the new”, this in turn we believe helps our customers not only drive ROI from the investments they have already made but also helps them innovate faster at lower risk and cost. Implementing Analytics into all our products is key to enabling our customers to maximize the ROI of their investment in Micro Focus technologies. This is the core of our customer centered innovation strategy and business model that we have successfully applied across our portfolio for more than 40 years. 

Ken Muir is the General Manager of the IDOL business line and VP of Operations and Security for Micro Focus’ Information Management and Governance Product Group.