The combination of cloud and AI has revolutionized the way businesses operate. With the help of cloud technology, enterprises can now move vast amounts of data and perform complex computations quickly. Automation has also advanced to a point where it is now powered by artificial intelligence. The latest innovation in AI is generative AI (Gen AI), which has been making waves for the past few years. With the advent of ChatGPT and Gemini, generative AI is becoming even more advanced, making artificial intelligence more powerful and human-like.

“70% Gen Z population report using some sort of Gen AI reaffirming that it is not just a futuristic trend, but a game-changer in getting things done.” 

Let’s begin by discussing the distinction between traditional AI and generative AI.

Decoding AI: Traditional vs. Generative

The shift from traditional AI to GenAI is not just an upgrade but a significant paradigm shift. Conventional AI works like a detective, analyzing data to make predictions and solve problems. In contrast, GenAI is like an artist who can use the same data to create new and unique content, thereby expanding the possibilities. 

Traditional AI relies heavily on pre-defined datasets and significant human intervention, whereas GenAI operates with a remarkable degree of autonomy. It can learn and evolve independently, generating new insights and content with minimal human input. This self-improvement capability sets GenAI apart, enabling it to become more effective and nuanced over time.

A McKinsey report shows businessess using generative AI report a 20% increase in efficiency and 15% boost in revenue” “Why not GenAI?”

The GenAI Revolution in Enterprise Analytics

Enterprise analytics can benefit significantly by shifting from a reactive approach to a proactive one, allowing for the creation of new and innovative solutions. This change in strategy opens up a whole new world of possibilities for growth and development, enabling organizations to stay ahead of the curve and succeed in today’s competitive business landscape.

GenAI’s key applications include:

Synthetic Data Generation:

  • The ability to test marketing campaigns or product designs without risking real customer data or spending money is now possible through Gen AI simulations for experiments, hypothesis testing, and alpha testing. 

Deep Insights Discovery:  

  • Gen AI can comprehend hidden trends, patterns, and connections among complex datasets that are beyond human abilities, providing deeper insights for data-driven decision-making. 

Customized Data Narratives:  

  • Many reports and dashboards can be challenging to understand due to the overwhelming amount of raw data. However, with the help of Gen AI, data can be presented more clearly and understandably. Custom reports can be tailored to the reader’s needs and level of understanding, with key findings summarized in simple language for easy comprehension. 

It’s fascinating to see how cloud providers like Oracle are taking a proactive approach to advance the capabilities of generative AI. By collaborating with various LLM providers, they are constantly working to improve its efficiency and accuracy. Oracle’s latest offering of generative AI services in Oracle Cloud Infrastructure (OCI) is a significant step forward in this regard. Through retrieval-augmented generation (RAG), these services can revolutionize the accuracy and relevancy of data sets for analytics.

Strategic Advantages of GenAI in OCI

Adopting GenAI within OCI offers a plethora of strategic benefits:

  • Innovation Acceleration: GenAI facilitates rapid experimentation, significantly shortening the innovation cycle and ensuring competitiveness. 
  • Enhanced Data Integrity: Sophisticated data cleaning and organization techniques improve the reliability and accuracy of analytics, aiding informed decision-making. 
  • Strategic Insight Revelation: GenAI’s ability to discern intricate data patterns unveils strategic insights, guiding informed and strategic business decisions. 

Moreover, OCI’s inclusive development environment, bolstered by low-code platforms and natural language processing, democratizes advanced analytics, enabling a broader spectrum of businesses to leverage their data fully.

GenAI in Action: Oracle Analytics Cloud

Generative AI development on OCI can be made much simpler by leveraging the platform’s capabilities. OCI’s high-performance, low-code Oracle Cloud Platform services and Natural Language Processing (NLP) can be used to create and deliver analytics platforms to customers. Oracle provides Generative AI through various LLMs like Cohere, Azure AI, and Meta, which can be accessed via API calls from OCI. Gen-AI is delivered to the dedicated OCI region running on high-performance infrastructure, making it ideal for enterprise analytics customers with strict regulations and compliance requirements. 

Oracle Autonomous Data Warehouse (OADW) and MySQL Heatwave databases are being prepared for Generative AI. These databases are equipped with VectorAI search capabilities that can be queried using LLM interfaces with natural language processing (NLP). MySQL Heatwave has been updated to support online analytical processing (OLAP) and online transaction processing (OLTP) using LLM interfaces and RAG capabilities. OADW integrates with LLMs using APIs, allowing SQL queries to be generated from natural queries. With RAG and LLM, customers using Oracle Analytics Cloud can obtain predictions without coding for AI and ML. They can request predictions, and the content will be generated for them. Developing Generative AI on OCI will easily siphon off most development complexities. OCI can be used to develop and deliver Analytics platforms to customers using the ‘high performing’ Low code Oracle Cloud Platform services and Natural Language Processing (NLP).

Preparing for the GenAI Revolution with Oracle’s Autonomous Data Warehouse and MySQL Heatwave

OCI’s key databases, Oracle Autonomous Data Warehouse (OADW) and MySQL Heatwave, are being prepared for Generative AI. They have built-in VectorAI search capabilities that can be queried through LLM interfaces using Natural Language Processing (NLP). MySQL Heatwave has been updated to support Online Analytical Processing (OLAP) and Online Transaction Processing (OLTP) using LLM interfaces and RAG capabilities. OADW integrates with LLMs through APIs, enabling SQL queries to be generated based on natural language queries. With RAG and LLM, Oracle Analytics Cloud customers can request predictions without coding for AI and ML. The system will generate content for them. 

Below is the simple architecture for Generative Artificial Intelligence on OCI:

Architecture for Generative Artificial Intelligence on OCI

Use case: Unleashing Generative AI’s Potential with Oracle Analytics Cloud

The following showcases dashboards created using Oracle Analytics Cloud (OAC). These dashboards can pull data from various sources, including ERP systems, data warehouses, CRM systems, Facebook, Google Analytics, and social media. We have utilized the OCI AutoML tool to predict sales patterns and customer churn, using several built-in algorithms like generalized linear models, random forests, and exponential smoothing. The output of these predictions is also displayed in the dashboards. 

The machine learning models created can be easily deployed from OAC and other applications.

OAC dashboard for Sales Forecast predicted using OracleML Algorithms

Make scientific predictions for future sales volume based on historical time stamped data.  Involves building models through historical analysis and using them to make observations and drive future strategic decision-making.  

Algorithms Used  

Holt-Winters, Multi season (MSLT)  

Parameters & Period   

Partition: Brand, Product Category, Product subcategory 

Period: Transaction Date (Two Years)  

Seasonality: 6 

OCI Machine learning service using inbuilt Models and Algorithms for Customer Churn Prediction

OCI has recently launched generative AI services with RAG and LLM capabilities. These services are designed to produce accurate and reliable output, such as sales reports, forecasts, product images, and beautiful OAC dashboards with the latest content. These dashboards can also be generated with self-generated content from social media. The AI services can also create effective training content for fine-tuning OAC dashboards and testing purposes.

“Boost innovation like 86% of businessess using AI – unlock the power to create, not just analyze, your data”

Conclusion and Future   

In today’s highly competitive business environment, having access to advanced analytics and artificial intelligence (AI) technologies can give enterprises a significant edge. Oracle Generative AI is one such solution that is gaining popularity due to its cost competitiveness and suitability for enterprise-grade analytics. 

With its recently launched RAG and LLM integrations, Oracle Generative AI offers businesses substantial benefits, enabling them to gain valuable insights from their data. The LLM is continuously improving, and Oracle is developing new UI tooling and AI Studio to make query writing, model training, and other tasks easier. 

Moreover, OCI Gen-AI runs on high-performing dedicated regions and Oracle Exadata Exascale databases that power OADW and MySQL heatwaves. This results in high performance and hardware cost optimizations. With these cutting-edge technologies, OCI Generative AI is revolutionizing enterprise analytics and other SaaS offerings. 

Are you ready to unlock the true potential of your data? If yes, book a demo today with Aspire Systems, the premium partner for Oracle Cloud Infrastructure. Discover how this transformative technology can propel your business to new heights. Let’s join the Generative AI revolution and explore the power of data together.