AI meet Data - Who wants to go up to 50% faster, anyone? This changes how we work with data and produce outputs.
The Common needs for Reporting in insurance are:
Operational
Regulatory
Exceptions
And Insights
Doing valuations at clients, the common themes in the data teams are:
Getting the data from source to a target environment
Wrangling and making sense of the data
Creating data repositories (warehouse) to make it more accessible
Apply business rules and logic to the data
Documentation
Reporting and Insights activities on the data.
Working through multiple use cases with AI and tie them to business domains, my clients continue to get remarkable results. Using #EnterpriseAI technology enables secure environments to business problems. Using #GoogleVertexAI and #AzureAI and the fine tuned AI specifically for data is the key to unlocking the innovation with data solutions #GeminiCode #GitHubCopilot
🔔 The key is prompting - and knowing what you want.
So what can we do with AI and Data, grounded on a business problem or requirement we can:
Simplifies the main components of data analysts and data engineers:
- Explain code
- Create code (SAS, SQL, Python etc)
- Rewrite code (From one language to another)
- Documentation (yes all of it)
Advanced AI and Data allows us to:
- Translate requirements into code
- Generate new insights and business recommendations
- Use Natural language to solve the business problem
Findings:
Up to 50% efficiency in explaining code and logic
Up to 60% efficiency in documentation of Source to Target , Impact Assessments, Business Rules and Documentation
Up to 30% Faster Code generation
Up to 30% faster code re-write from one language to another
Overall Improvement in User Experience and satisfaction
If you want to get your data team moving quicker, and using technology to augment their outputs, send us a message and we will love to work with you.
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