What is NLP Natural Language Processing is a specialized subdomain of Machine Learning which is generally concerned with the interactions between the human and machine using a human verbal or written language. NLP helps in processing huge volumes of text which would take a significant amount of time for a human to comprehend and process otherwise. Hence a lot of organizations take advantage of NLP to gain useful insights out of their text and free formatted data.

In this blog, we will walk through the scenario of sending or E-bonding ServiceNow incidents to 5 destinations simultaneously, using Robotic Data Automation and AIOps Studio. E-bonding refers to a scenario where data is delivered (one-way) or synchronized (two-way) between two or different systems, which are typically under different administrative boundaries. E-Bonding term originally appeared in Service Provider and Telco space (see: ATT E-Bonding).

Implementing any IT project requires time, planning, and effort and AIOps probably requires even more planning and stakeholder involvement, because of the breadth of coverage and potential to bring profits to multiple IT domains/functions (ex: ITOps/ITSM/NOCOps). Customers have high expectations from AIOps, but, even after taking such major projects, most AIOps vendors are only able to support a few core AIOps use cases, which severely limits the utility and potential of AIOps.

Lately, I have seen fewer call outs from our field teams to our solution engineering team, and I was wondering what could be the reason? Sometimes, our field engineers approach our solution engineering team with advanced requests for data analysis, running what-if scenarios and assessing the quality of data and what new value can be gleaned by combining related datasets.

As businesses become increasingly digital, IT operations now deal with more extensive and more complex data than before. Traditional tools and strategies might no longer be enough to help them cope with their growing workload. Hence, many organizations are tuning in to the various AIOps trends available. AIOps is short for Artificial Intelligence (AI) for IT Operations. This is where they use Machine Learning(ML) to enhance and automate IT functions.

RDA enables enterprises to operationalize machine data at scale to drive AI & analytics driven decisions. RDA automates repetitive data integration, preparation and transformation activities using bots that are invoked in “no-code” data workflows or pipelines. RDA helps to move data in and out of AIOps systems thereby simplifying and accelerating AIOps implementations that otherwise would depend numerous manual data integrations and professional services activities.

Complexity breaks correlation. Intelligence brings cohesion. This simple principle is what makes real-time asset intelligence a must-have for AIOps that is meant to diffuse complexity. To further create a context for the user, it is critical to understand service dependencies and correlate alerts across the stack to resolve incidents. CMDB systems have been useful to break down configuration items into logical layers. But, that’s not enough because they can become outdated very soon.