5 Tips for BI Dashboarding in Coveo
Defining Clear Objectives: Before diving into the data, determine what you want to achieve with your dashboard. This could be understanding customer behavior, measuring content performance, or improving search effectiveness. Understanding Key Metrics: Identify which metrics are most important for your goals. Examples include click-through rates, query abandonment rates, or time spent on page. Knowing these will guide your analysis. Segmenting Data: Break down your data into smaller segments; such as, user demographics, behavior types, or time periods. This will allow for more targeted analysis and actionable insights. Using Visualizations Effectively: Choose the right visualizations to represent your data. Bar graphs, line charts, heat maps, or even scatter plots can help you recognize patterns and trends more easily. Leveraging Machine Learning Insights: Use Coveo's machine learning capabilities to uncover deeper insights, like content gaps or unexpected user search patterns, that might not be immediately apparent from raw data alone. These tips are designed to maximize the utility of Coveo's analytics dashboards by providing a structured approach to data analysis.What do you consider a modern BI platform and why?
What makes a modern BI data visualization platform feel modern? Whether it's business intelligence or insights, we've come a long way over the years with options for adoption of BI platforms. What features do you consider modern these days and what platforms do you look to when pushing the boundaries of innovation in the BI space today?AI features in Power BI
Data Preparation You can enrich your text data with text analytics, analyze sentiment, analyze sentiment, identify key phrases, and detect languages in your text data. With Power BI vision feature you can tag your images, detect your images, and extract text from the images. Both these features need Power BI premium as they use pre-trained Machine Learning Models from Azure Cognitive Services. Data Analysis Power BI offers various AI capabilities and visuals for both developers and business users. Business users can use natural language to query data and examine reports with AI-driven visualizations. With AI driven visuals like key influencers, smart narrative, decomposition tree users can discover hidden insights in the data. Features like anomaly detection, forecasting, and integration with Azure Cognitive Services can identify unexpected patterns, predict future outcomes, and use custom ML models in Power BI. Data Visualization Smart Discovery enables Power BI to automatically discover and visualize your data, it is enabled and delivered through AI. This is also available in different forms within Microsoft Ecosystem. With Natural Language Query in Power BI, you can directly type your question and get quick answers and insights about your data. Preview Features Microsoft Copilot will expand Power BI's AI capabilities, including generating DAX formulas from natural language.
