Written By: Associate Vice President, Analytics and Data Strategy, Quantzig.
Table of Contents
Table of Content:
- AI in Business Intelligence
- Quantzig’s Approach to AI in BI
- How Business Intelligence Work?
- Quantzig’s Tech Stack for AI in BI
- Why is Business Intelligence Important?
- Key Benefits of AI in BI
- Upgrade Business Intelligence Solutions with AI
- Quantzig Case Study: Simplifying Insights for a UK-Based CPG Client
- Other Use Cases of AI in Business Intelligence Across Industries
- How Quantzig Solution helps to Integrate AI into Business Intelligence
- Why Choose Quantzig?
AI in Business Intelligence (BI)
AI in BI, or Artificial Intelligence in Business Intelligence, refers to the application of machine learning and other AI techniques to enhance traditional BI practices. Traditionally, BI has focused on analyzing past data to understand what has happened. AI injects a future-focused element by leveraging machine learning algorithms to uncover hidden patterns, predict trends, and automate tasks. This empowers businesses to make more proactive and data-driven decisions. The primary goal of BI is to provide organizations with actionable insights that can help them improve operational efficiency, identify new opportunities, and gain a competitive advantage.
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How Quantzig Enables AI in BI?
Quantzig, a leader in analytics and data strategy, enables AI in BI through three key approaches:
Enabling AI within Individual Assets
- For example, incorporating AI functionalities such as CoPilot within a PowerBI Dashboard.
AI Layer for Integrated Insights
- An AI layer that sits on top of multiple data sets and assets, functioning as a control tower linking derived insights from across dashboards, reports, or data sets.
Building a Completely New AI Engine
- Developing a new LLM (Large Language Model) or RAG (Retrieval-Augmented Generation) with customized semantic models and foundational setups to implement an independent AI engine.
How Does Business Intelligence Work?
BI systems typically involve the following key components:
Quantzig’s Tech Stack for AI in BI
Quantzig leverages a robust tech stack to deliver AI-driven BI solutions:
- CoPilot & Fabric in Microsoft: Integrates AI capabilities within Microsoft PowerBI to enhance data visualization and insights.
- Tableau AI: Utilizes AI-driven analytics to provide deeper insights and improve decision-making within Tableau dashboards.
- Domo: Leverages AI & Advanced Analytics to automate data integration, preparation, and analysis, delivering real-time insights across various business functions.
- SAP Hana: Employs AI and machine learning to process large volumes of data, delivering advanced analytics and real-time insights for enterprise applications.
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Request a Free PilotWhy is Business Intelligence Important?
There are several key reasons why business intelligence is crucial for modern organizations:
- Competitive Advantage: BI provides organizations with real-time insights into their operations, customers, and market trends, allowing them to make informed decisions and stay ahead of the competition.
- Improved Decision-Making: BI empowers decision-makers with accurate and timely data, enabling them to identify trends, patterns, and opportunities that might not be apparent otherwise.
- Enhanced Operational Efficiency: BI can help organizations streamline their operations by identifying inefficiencies and areas for improvement, leading to cost savings and increased productivity.
- Deeper Customer Insights: BI can provide valuable insights into customer behavior, preferences, and trends, allowing organizations to tailor their products and services to better meet customer needs.
- Predictive Capabilities: BI can help organizations predict future trends and events by analyzing historical data, enabling them to make proactive decisions and mitigate risks.
- Real-Time Reporting: BI can enhance an organization’s reporting capabilities by providing access to real-time data, allowing for faster decision-making and improved responsiveness to changing market conditions.
Key Benefits of AI in BI
Generating Insight: Massive datasets hold hidden connections and trends. AI algorithms can process large and complex datasets, uncovering these macro and micro insights at scale.
Predictive Foresights: By analyzing data and identifying patterns, AI can predict future trends, allowing businesses to take proactive measures and capitalize on opportunities.
Workflow Automation: AI automates many repetitive tasks involved in data preparation and analysis, streamlining processes and increasing efficiency.
Cognitive Consumption: AI-powered BI tools can be designed with user-friendly interfaces and cognitive data consumptions through low code/no code/no chart BI consumption models. This makes data insights more accessible and actionable for users across the organization.
Upgrade Business Intelligence Solutions with AI
Artificial Intelligence (AI) and machine learning (ML) are transforming the landscape of business intelligence, unlocking new levels of insights and decision-making capabilities. By integrating AI into BI solutions, organizations can:
- Automate Data Preparation: AI-powered tools can automate the process of data extraction, cleaning, and integration, reducing the time and effort required for data preparation.
- Enhance Data Analysis: AI algorithms can identify complex patterns and relationships within data, enabling more sophisticated and predictive analytics.
- Improve Forecasting: AI-driven predictive analytics can help organizations make more accurate forecasts about future trends, customer behavior, and market conditions.
- Personalize Insights: AI can personalize the presentation of insights and recommendations based on the user’s role, preferences, and decision-making context.
Quantzig Case Study: Simplifying Insights for a UK-Based CPG Client
| Criteria | Definition |
|---|---|
| Client Overview | UK-based CPG company focused on healthcare and nutrition. |
| Challenge | Simplify and summarize insight generation for executive consumption. |
| Solution | PowerBI upgrades with CoPilot widgets and creation of semantic models and data pipelines for AI engine. |
| Impact Delivered | Phase 1 completed in 12 weeks, Phase 2 completed in 10 weeks. |
Client Overview
The client is a UK-based Consumer Packaged Goods (CPG) company focusing on healthcare and nutrition. They faced challenges with their existing dashboards and data assets, which were too detailed for executive consumption. They sought to simplify and summarize insight generation and call to actions through advanced technology solutions.
The Challenge faced by the Client
The client needed a solution to streamline their extensive data and make insights more accessible and actionable for executives. Their goal was to have faster access to data and simplified insight generation without the need for complex dashboard interactions.
The Solution Quantzig Incorporated
Quantzig partnered with the client on a Data Modernization & AI Transformation initiative. The approach included:
- PowerBI Dashboard Upgrades: Enhanced with CoPilot widgets for in-dashboard AI consumption.
- Semantic Models and Data Pipelines: Created to focus on day-to-day performance and measure POS (Point of Sale) performance through a dedicated AI engine.
Implementation Timeline
- Phase 1: Completed within 12 weeks.
- Phase 2: Completed within 10 weeks.
Impact Delivered
Cognitive Access to Data: Faster access to data for citizen consumers without the need for extensive dashboard interaction.
Optimized Response Time: Queries response time optimized to an SLA (Service Level Agreement) of 15-45 seconds.
Other Use Cases of AI in Business Intelligence Across Industries
Advanced technologies like AI (Artificial Intelligence) and BI (Business Intelligence) to gain a competitive edge. Traditional BI methods, which rely on manual data gathering, cleaning standardization, storage, analysis, and visualization, are being augmented by AI-enabled BI solutions. These cutting-edge tools leverage big data, deep learning, and advanced data analytics to uncover hidden insights and patterns. By harnessing the power of custom AI solutions, various businesses can make more informed strategic decisions, ultimately leading to a stronger competitive advantage in their markets, including:
Finance
Investment Analysis: AI-powered tools can analyze vast amounts of financial data to identify investment opportunities and optimize portfolio management.
Fraud Detection: AI algorithms can detect patterns of fraudulent activity in financial transactions, helping organizations mitigate risks and protect their assets.
Marketing
Customer Segmentation: AI can help organizations segment their customer base more effectively, enabling personalized marketing campaigns and improved customer engagement.
Predictive Lead Scoring: AI-driven predictive analytics can help sales and marketing teams identify the most promising leads, leading to higher conversion rates.
Healthcare
Clinical Decision Support: AI-powered BI tools can analyze patient data and medical literature to provide healthcare professionals with real-time insights and recommendations for improved patient outcomes.
Supply Chain Optimization: AI can help healthcare organizations optimize their supply chains, reducing waste and ensuring the availability of critical medical supplies.
How Quantzig Solution helps to Integrate AI into Business Intelligence?
Integrating AI into business intelligence typically involves the following steps:
- Assess Current BI Capabilities: Evaluate the organization’s existing BI infrastructure, data sources, and analytical capabilities to identify areas where AI can be leveraged.
- Define AI Use Cases: Collaborate with business stakeholders to identify specific use cases where AI-powered BI can deliver the most value, such as predictive analytics, customer segmentation, or supply chain optimization.
- Develop an AI Strategy: Establish a clear roadmap for AI integration, including data management, model development, deployment, and ongoing monitoring and maintenance.
- Implement AI-Powered BI Tools: Evaluate and select BI platforms that offer robust AI and machine learning capabilities, such as automated data preparation, natural language processing, and prescriptive analytics.
- Ensure Data Readiness: Invest in data quality, governance, and integration efforts to ensure that the data powering the AI-driven BI system is accurate, complete, and accessible.
- Train and Upskill Employees: Provide comprehensive training and support to help employees understand and effectively utilize the AI-powered BI tools and insights.
- Continuously Optimize and Iterate: Regularly review the performance and impact of the AI-powered BI system, and make adjustments to the models, data sources, and user interfaces as needed.
By integrating AI into their business intelligence strategies, organizations can unlock new levels of insights, decision-making capabilities, and competitive advantage in today’s data-driven business landscape.
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Start your Free Trial todayWhy Choose Quantzig?
Traditional BI systems have evolved significantly with the advent of AI-enabled BI, which enhances every stage of the BI process. From data gathering and data cleaning/standardization to data storage and data analysis, AI tools streamline workflows and improve accuracy. Data visualization becomes more insightful, aiding in strategic planning and offering a competitive advantage. Organizations increasingly seek custom AI solutions and advanced data analytics to harness big data and leverage deep learning techniques. AI (Artificial Intelligence) is revolutionizing BI (Business Intelligence) by transforming raw data into actionable insights, driving better business decisions.
Quantzig stands out as an expert in AI-driven BI solutions, providing tailored strategies that align with your organization’s unique needs. With a proven track record in enhancing data quality, generating actionable insights, and improving decision-making processes, Quantzig ensures your business stays ahead of the competition in a data-driven world.
