Like many millennials, one of my favorite video game was Mario. The most satisfying thing about Super Mario were the power-up mushrooms - that gave it added abilities, to keep conquering world after world. Similarly, today when data and information are created at an accelerating rate, outstripping the ability of humans to keep up - it becomes imperative for enterprise operations to enable a digital workforce to achieve demonstrable gains in efficiency and productivity.
Operational Analytics, with subjective experience, is indeed very much useful - but it's more inclined towards Descriptive Analytics, based on what has already happened in the past. With Predictive Analytics, it opens up a whole new world where we can design algorithms to detect complex pattern - and provide powerful insights to predict the future. The more powerful our mathematical algorithm, and the more robust our datasets, the better we get with our statistical and strategic inferences.
With a journey that started few months back with analyzing and synthesizing vast amounts of logs generated by Oracle BI Apps, Oracle Hyperion Essbase, and Oracle Data Integrator, it's fascinating to see how today unprecedented levels of efficiency and quality can be achieved by transcending conventional performance tradeoffs. Let's coin in the term Intelligent Process Automation here - since it will not be fair to navigate this picturesque landscape without getting a deep feel of the next-gen tools forming the core of this cognitive technical process.
How does IPA fit in our ODI BI Apps Power-Up? Well, wait for it, let's put it out there in as much crispy and munchy (reminding me of chocolate chip cookies...umm..) way as possible. We get to know the answers to all the following questions today, in near real-time. When does the application encounter "ODI-10188: Error while login from OPSS" due to Authentication issues which causes critical Production ODI jobs to fail? When does the application face errors due to "Unable to create connection to LDAP" which creates fatal scenarios in complex running processes? When does the application face errors like "LDAP response read timed out" which causes ODI jobs or online OBIEE reports to error out? Can our IPA model figure out what went wrong by itself and let me know?
Now, let's see what happens when we create a model that will continuously "teach" our "agent" to "learn" from the stream of situational data, analyze the same, and respond to complex queries. What happens when we inject decision-making capabilities to enhance our "agent", such that it is able to learn and adapt with time? We start getting answers to all the following questions - how stable does the system look? Since applications and jobs running fine does not necessarily indicate everything is fine, should we be aware of any "indicators" that can serve as giving us predictive information of the future state? Why is the application or system behavior the way it is now? Which teams need to be involved right away when the system behaves in a specific pattern? Can the system auto-heal given a specific scenario and then share that information? When can we anticipate a specific good news scenario that happened in the past? How can we predict a major upcoming issue that has happened in the past? How close are we to reaching our specific target figures?
Thus, with the interplay of concepts, technologies, it's fascinating to see how we are able to create strategic assets, helping us achieve unprecedented levels of efficiency, control, quality, and most importantly, speed - which is definitely poised to transform the existing workforce, with radically enhanced response times, and ofcourse, reduced operational risks.
Really fantastic visual appeal on this web site, I'd rate it 10.
I could not refrain from commenting. Very well written!
Goοd post. I'm dealing with some of these issues as well..
Very good post. I'm dealing with a few of these issues as well..
Hey There. I found your blog using msn. This is an extremely well written article.I will be sure to bookmark it and come back to read more of your useful information. Thanks for the post. I will definitely return.
I went over this website and I think you have a lot of superb info, saved to bookmarks (:.