Received deeper insights from mentors, trade consultants, and numerous research supplies

I’m Dhiman Deb, working as Software program Improvement Engineer II at Oracle with the Knowledge and Analytics product growth staff for the final 2 years. My whole expertise within the trade is 7+ years, spanned throughout a number of enterprise domains akin to Banking & Retail, Oil and Gasoline, Provide Chain, Telecom, and so forth. 

At Oracle, I work with the product growth staff to develop new options and functionalities to allow prospects to have a greater expertise within the Provide chain space, ranging from Order to Money, Procurement, Order administration, put in base, Upkeep, and so forth., utilizing numerous instruments akin to OBIEE, Oracle Analytics Cloud and applied sciences akin to Machine Studying, Synthetic Intelligence, Course of Automation utilizing Python, Scala & Spark, and so forth. We now have noticed that we are able to higher equip the shopper to inventory their stock based mostly on the expertise with the provider and their supply efficiency.

We now have been utilizing numerous applied sciences to arrange an information pipeline and feed the information to analytics purposes for Machine studying consumption. Supply knowledge is getting injected from a number of supply methods akin to CSV and Oracle databases into an information warehouse utilizing Oracle Knowledge Integrator (ODI). We now have accomplished numerous knowledge manipulation steps on supply knowledge utilizing ODI inbuilt transformation. Then remodeled knowledge obtained pushed into the Knowledge movement of Oracle Analytics Cloud (OAC), and a pre-built & examined Machine Studying mannequin (Numerical prediction) was used to forecast future demand. Later we visualized the prediction utilizing the OAC knowledge visualization instrument.

There are two eventualities significantly: I’ve utilized AI/ML aside from numerous small/medium initiatives the place I’ve used python to automate or construct instruments for the group for higher buyer expertise.

Within the first state of affairs, the place I’ve used the BERT mannequin together with my staff members to develop an NLP resolution that may present Oracle-specific solutions and hyperlinks to paperwork for numerous analytical and business-related questions.

On the second, the place we are attempting to determine future demand based mostly upon numerous parameters akin to season, previous years’ demand, and so forth.

Thus far, we now have achieved 80% accuracy with the present mannequin, and all the knowledge pipeline is performing as per expectation. We now have additionally labeled suppliers into numerous segments based mostly on the supply timeline, akin to on-time, late or early.

The entire resolution has been examined and demoed to a peer group and printed over the Oracle market for the consumption of assorted Oracle prospects.

I’ve simply began Nice Studying’s PGP Synthetic Intelligence and Machine Studying Course. Nonetheless, in a really brief span, I’m able to brush up on my expertise in addition to get deeper insights from mentors, trade consultants, and numerous research supplies.