New AI Capabilities with Oracle Analytics

IPSpecialist
7 min readFeb 19, 2024

Introduction

Explore the forefront of the data analysis revolution with Oracle Analytics, a trailblazer in integrating Artificial Intelligence (AI) capabilities. This blog unravels the transformative impact of cutting-edge features such as advanced predictive analytics, natural language processing, automated data preparation, and explainable AI. Oracle Analytics keeps pace with the AI revolution and sets new standards, redefining how users at all levels engage with their data. This blog invites readers to discover the intelligent, intuitive, and impactful world of Oracle Analytics, where AI is not just a feature but a driving force reshaping the data analysis landscape.

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Oracle Analytics offers various AI capabilities and consistently innovates throughout the year. It offers customers capabilities enhanced by AI, ML, and DS and uses AI services linked with Oracle Cloud Infrastructure (OCI). This blog is all about new AI capabilities with Oracle analytics.

Oracle Analytics provides three categories of AI functionalities:

  • Built-in, AI-augmented capabilities
  • Integrated ML capabilities
  • Integrated AI capabilities
  1. Built-in, AI-Augmented Capabilities:

Oracle Analytics seamlessly integrates AI into its core functionalities, revolutionizing the user experience by introducing intelligent features that automate and optimize various aspects of data analysis.

AI Auto-Insights:

The AI Auto-Insights feature represents a paradigm shift in data exploration. By automating the generation of optimal visualizations based on selected datasets, this functionality eliminates the need for extensive manual analysis. The system intelligently identifies patterns, trends, and outliers, providing users with visual insights typically requiring significant time and effort to uncover.

Benefits:

  • Time Efficiency: Saves considerable time spent on manual exploration, allowing users to focus on deriving meaningful insights.
  • Pattern Recognition: Uncovers hidden patterns and trends within the data, offering a quick and efficient way to understand the underlying structure of the information.
  • Actionable Insights: Provides users with actionable insights, enabling prompt decision-making based on visualizations tailored to the dataset’s characteristics.

AI Explain:

The AI Explain feature adds a layer of transparency to data analysis. With a single click, users can delve into the intricacies of the data, gaining insights into the key factors and correlations that influence specific metrics. This transparency enhances understanding and facilitates informed, data-driven decision-making by demystifying the relationships within the dataset.

Benefits:

  • Transparency: A clear and transparent view of the factors influencing specific metrics builds trust in the analytical process.
  • Deeper Understanding: Fosters a deeper understanding of the data, empowering users to interpret and act upon insights confidently.
  • Data-Driven Decision Making: This enables users to make informed decisions based on a comprehensive understanding of the underlying data dynamics, improving the overall quality of decision-making processes.

2. Integrated ML Capabilities:

Oracle Analytics seamlessly integrates machine learning (ML) capabilities directly into its platform, offering users the ability to harness powerful algorithms without the necessity of extensive coding expertise. This integration democratizes advanced analytics, making it accessible to a broader user base.

1-Click ML/AI:

The 1-Click ML/AI feature represents a revolutionary approach to machine learning, breaking down barriers by allowing users to create forecasts and clusters with a single click. By leveraging sophisticated algorithms such as ARIMA and ETS, this functionality simplifies the traditionally complex process of machine learning, eliminating the need for users to possess advanced coding skills.

Benefits:

  • Democratization of ML: Enables users without extensive coding expertise to harness the power of machine learning effortlessly.
  • Ease of Use: Simplifies the creation of forecasts and clusters, making advanced analytics more accessible to a broader audience.
  • Efficiency: Reduces the time and effort required for traditional machine learning tasks, fostering a more efficient analytics workflow.

Predictive Analytics:

The Predictive Analytics feature empowers users to make informed decisions by utilizing machine learning algorithms for accurate predictions based on historical data. Organizations can anticipate future developments by analyzing patterns and trends, enabling proactive decision-making and strategic planning.

Benefits:

  • Accurate Predictions: Utilizes machine learning algorithms to generate accurate predictions based on historical data, improving the reliability of forecasting.
  • Trend Anticipation: This helps organizations anticipate trends, keeping them ahead of market shifts and evolving customer behaviors.
  • Informed Decision Making: Enhances decision-making processes by providing valuable insights into future outcomes, guiding organizations towards data-driven strategies.

3. Integrated AI Capabilities:

Oracle Analytics seamlessly integrates advanced AI functionalities, providing users with a holistic approach to harnessing the full potential of artificial intelligence within the analytics workflow. This integration goes beyond mere augmentation, offering sophisticated features that enhance predictive modeling and enable natural language interactions.

Advanced Predictive Analytics:

The Advanced Predictive Analytics feature is at the forefront of Oracle Analytics’ integrated AI capabilities. Leveraging artificial intelligence, this functionality enables users to conduct more sophisticated predictive modeling. By utilizing advanced algorithms and techniques, users can make accurate predictions and identify intricate patterns within their data. This goes beyond traditional predictive analytics, providing a more nuanced understanding of complex data relationships.

Benefits:

  • Enhanced Accuracy: The integration of AI elevates the accuracy of predictions, ensuring that organizations can rely on data-driven insights for strategic decision-making.
  • Deeper Understanding: By unraveling complex data relationships, users gain a more profound understanding of the factors influencing outcomes, fostering more informed and strategic decision-making.

Natural Language Processing (NLP):

The Natural Language Processing (NLP) feature within Oracle Analytics transforms how users interact with data. This functionality facilitates conversational analytics by allowing users to engage with the platform using everyday language. Regardless of their technical background, users can query and analyze data effortlessly, breaking down barriers and making analytics more accessible to a broader audience.

Benefits:

  • Conversational Analytics: NLP enables a natural and conversational interaction with data, allowing users to pose questions and receive insights in plain language.
  • Accessibility: The feature enhances accessibility by enabling individuals without a deep technical background to engage with analytics, expanding the user base and promoting collaboration.

Exciting Future with New AI Capabilities in Oracle Analytics

Oracle Analytics is making waves by integrating cutting-edge AI into its platform, empowering users with powerful new capabilities. Here’s a glimpse into the future scope of this exciting fusion:

  1. Deeper Insights and Automation:
  • Intelligent Question Answering: Imagine asking open-ended questions about your data and getting insights delivered through natural language interactions. AI digital assistants, like the one planned for integration with Cohere LLMs, will make this a reality.
  • Automated Anomaly Detection: AI will proactively scan your data for anomalies, automatically flagging potential issues and saving you time from manual analysis.
  • Hyper-personalized Analytics: AI will tailor dashboards and reports to individual users, surfacing relevant information based on their roles and responsibilities.

2. Enhanced Data Storytelling:

  • AI-powered Data Visualization: AI will suggest optimal chart types and layouts based on your data, creating clear and impactful visualizations that resonate with your audience.
  • Automated Story Generation: AI will analyze your data and automatically generate insightful narratives, turning complex numbers into compelling stories that drive action.
  • Photorealistic Avatars for Data Delivery: Imagine engaging AI-generated avatars presenting your data insights in a captivating way, fostering better communication and understanding.

3. Democratizing Data Science:

  • Low-code/No-code AI Tools: Users with limited technical expertise will be able to leverage AI-powered features for analysis, democratizing data science across the organization.
  • Explainable AI (XAI): AI models will be able to explain their reasoning, ensuring transparency and trust in their predictions.
  • Automated Feature Engineering: Tedious tasks like data preparation and feature engineering will be automated by AI, freeing up data scientists for higher-level analysis.

4. Continuous Innovation:

  • Integration with Cutting-edge AI Technologies: Oracle is committed to staying ahead of the curve by integrating the latest advancements in AI, such as generative AI and natural language processing, into its platform.
  • Collaboration with Leading AI Experts: Ongoing partnerships with industry leaders will ensure Oracle Analytics remains at the forefront of AI-powered analytics.
  • Openness and Flexibility: The platform will remain open and flexible, allowing users to leverage external AI tools and services within their analytics workflows.

Conclusion

In the ever-evolving data analysis landscape, Oracle Analytics is a trailblazer, harnessing the transformative power of Artificial Intelligence (AI) across three key dimensions. The Built-in, AI-augmented capabilities streamline data exploration, automating insights and fostering transparency with features like AI Auto-Insights and AI Explain. Integrated ML Capabilities democratize machine learning, enabling users to effortlessly leverage powerful algorithms for predictive analytics with features like 1-Click ML/AI and Predictive Analytics. Integrating Advanced AI Capabilities takes analytics to new heights, offering sophisticated predictive modeling and natural language interaction through features like Advanced Predictive Analytics and Natural Language Processing (NLP). Through these innovations, Oracle Analytics not only enhances efficiency and accuracy but also ensures inclusivity, making data analysis accessible to a broader audience.

FAQs:

Q1: How does Oracle Analytics make advanced analytics accessible to users without coding expertise?

Answer:

Oracle Analytics achieves this through the 1-Click ML/AI feature, democratizing machine learning by allowing users to create forecasts and clusters with a single click. This eliminates the need for extensive coding, making advanced analytics accessible to a broader user base.

Q2: How does Oracle Analytics foster transparency in data analysis?

Answer:

The AI Explain feature plays a crucial role in fostering transparency. Users can delve into the data with a single click, revealing key factors and correlations influencing specific metrics. This transparency enhances understanding and facilitates informed, data-driven decision-making.

Q3: How does Oracle Analytics leverage AI for more sophisticated predictive modeling?

Answer:

The Advanced Predictive Analytics feature in Oracle Analytics leverages AI to conduct more sophisticated predictive modeling. This involves using advanced algorithms to make accurate predictions and identify intricate patterns within the data, providing users with a deeper understanding of complex data relationships.

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