Create Stunning Excel Dashboards in Seconds with AI : You Won't Believe How Easy It Is
What if creating an interactive Excel dashboard didn't take hours of manual effort or advanced technical skills? Imagine transforming raw data into a polished, dynamic visualization in mere seconds—all with the help of artificial intelligence. The rise of AI-powered tools is transforming how we approach data visualization, offering an unprecedented combination of speed and simplicity. But here's the catch: not all tools are created equal. While some excel in automation, others fall short in customization or handling complex datasets. This piece explores how AI is reshaping dashboard creation, shedding light on its potential and pitfalls.
In the following sections, Kenji explains how tools like Bricks, Claude, ChatGPT, and Microsoft Copilot stack up against traditional options like PowerBI. Whether you're looking for lightning-fast automation or advanced customization for Excel-based workflows, this guide will help you navigate the strengths and limitations of each tool. Along the way, we'll uncover practical tips for choosing the right solution for your needs, from handling large datasets to safeguarding sensitive information. The question isn't just how fast you can create a dashboard, but how effectively you can turn your data into actionable insights. AI Dashboard Creation Guide AI Tools for Dashboard Creation
AI tools are designed to simplify and accelerate the process of creating dashboards, but each tool has distinct features and limitations that influence its effectiveness. Here's a closer look at four popular options: Bricks: Renowned for its speed, Bricks can generate dashboards in seconds with minimal input. It offers basic customization options for visuals and titles, making it highly user-friendly. However, it lacks integration with widely-used platforms like Excel and PowerBI, and its performance diminishes when handling large datasets.
Renowned for its speed, Bricks can generate dashboards in seconds with minimal input. It offers basic customization options for visuals and titles, making it highly user-friendly. However, it lacks integration with widely-used platforms like Excel and PowerBI, and its performance diminishes when handling large datasets. Claude: This tool excels at generating key performance indicators (KPIs) and providing visual suggestions based on user prompts. While it can deliver insightful results, it requires precise instructions to maintain consistency. Additionally, Claude does not allow direct editing of dashboards, which limits its flexibility for iterative projects.
This tool excels at generating key performance indicators (KPIs) and providing visual suggestions based on user prompts. While it can deliver insightful results, it requires precise instructions to maintain consistency. Additionally, Claude does not allow direct editing of dashboards, which limits its flexibility for iterative projects. ChatGPT: ChatGPT supports basic dashboard creation using HTML and JavaScript. While suitable for simple projects, its output often lacks the sophistication and interactivity required for professional use. Its limited visualization capabilities further restrict its utility for complex tasks.
ChatGPT supports basic dashboard creation using HTML and JavaScript. While suitable for simple projects, its output often lacks the sophistication and interactivity required for professional use. Its limited visualization capabilities further restrict its utility for complex tasks. Microsoft Copilot: Integrated into Excel, Microsoft Copilot assists with data analysis and dashboard creation. While it offers seamless integration with Excel, it struggles with complex datasets and provides limited functionality for creating fully interactive dashboards.
Each of these tools has its niche, but understanding their specific capabilities is critical to selecting the right one for your needs. Interactive Data Visualization
Interactive dashboards are invaluable for exploring data dynamically, uncovering trends, and deriving actionable insights. AI tools have made significant strides in this area, but the level of interactivity they offer varies widely: Bricks and Claude: These tools prioritize automation, allowing users to create dashboards quickly. However, their limited customization options can be a drawback for projects requiring tailored visualizations.
These tools prioritize automation, allowing users to create dashboards quickly. However, their limited customization options can be a drawback for projects requiring tailored visualizations. PowerBI: In contrast, PowerBI offers advanced customization features, allowing users to adapt dashboards to specific business needs. Its robust interactivity makes it a preferred choice for professionals seeking detailed and dynamic visualizations.
When choosing a tool, it's important to consider the level of interactivity required for your project and whether the tool can meet those demands effectively. AI Tools That Create Excel Dashboards in Seconds
Watch this video on YouTube.
Dive deeper into Excel interactive dashboards with other articles and guides we have written below. Excel Integration and Compatibility
Excel remains a cornerstone of data analysis for many organizations, making compatibility with Excel a crucial factor when evaluating dashboard creation tools. Among the tools discussed: Microsoft Copilot: This tool offers the closest integration with Excel, making it a convenient choice for users already familiar with Excel workflows. However, its limited functionality for creating interactive dashboards may restrict its usefulness for more complex projects.
This tool offers the closest integration with Excel, making it a convenient choice for users already familiar with Excel workflows. However, its limited functionality for creating interactive dashboards may restrict its usefulness for more complex projects. Bricks and Claude: These tools lack direct integration with Excel, which can be a significant drawback for organizations that rely heavily on Excel for data management and analysis.
These tools lack direct integration with Excel, which can be a significant drawback for organizations that rely heavily on Excel for data management and analysis. PowerBI: PowerBI seamlessly integrates with Excel, allowing users to import data effortlessly and create sophisticated dashboards. This compatibility makes it a versatile and reliable option for professionals working with Excel-based datasets.
For businesses that depend on Excel, tools like PowerBI provide a more robust and adaptable solution compared to AI-driven alternatives. Challenges with Large Datasets
Handling large datasets is a common challenge for AI tools, and their performance can vary significantly depending on the tool and the complexity of the data: Bricks and Claude: These tools often struggle with large datasets, leading to incomplete outputs or performance issues. Their limitations make them less suitable for projects involving extensive data analysis.
These tools often struggle with large datasets, leading to incomplete outputs or performance issues. Their limitations make them less suitable for projects involving extensive data analysis. PowerBI: PowerBI is better equipped to handle large datasets, offering advanced data processing capabilities. However, it requires manual effort for data cleaning and preparation, which can be time-consuming but ensures accuracy and reliability.
For projects involving substantial datasets, tools like PowerBI, with their robust processing capabilities, are often the most dependable choice. Privacy Concerns in AI Data Processing
Privacy is a critical consideration when using AI tools for dashboard creation, as many of these tools require users to upload sensitive data. This raises concerns about data security and compliance with regulations such as GDPR. To address these concerns, it's essential to: Review the data handling policies of the AI tool to ensure they align with your organization's privacy standards.
Verify that the tool complies with relevant data protection regulations, such as GDPR or CCPA.
Assess whether sensitive data can be securely processed within the platform without exposing it to unnecessary risks.
Taking these precautions can help safeguard your organization's data and ensure compliance with privacy requirements. PowerBI: A Reliable Alternative
For professionals seeking a robust and reliable tool for dashboard creation, PowerBI remains a leading choice. It offers a range of advanced features that make it well-suited for complex projects, including: Comprehensive data cleaning and preparation tools.
Highly customizable visualizations to meet specific business needs.
Support for complex formulas and calculations using DAX (Data Analysis Expressions).
PowerBI's ability to handle large datasets and deliver high-quality, interactive dashboards has made it a preferred choice for many Fortune 500 companies. While it requires more manual effort compared to AI tools, the results are often superior in terms of accuracy, customization, and reliability. Manual Dashboard Creation Techniques
Despite the advancements in AI, manual dashboard creation remains a viable and often necessary option for many professionals. Tools like Excel and PowerBI provide the flexibility and control needed to create dashboards tailored to specific business requirements. While this approach may take more time, it offers several advantages: Greater precision and reliability in data processing and visualization.
Full control over the design and functionality of the dashboard.
The ability to create custom solutions for unique project needs.
For critical projects where accuracy and customization are paramount, manual methods often deliver the most dependable results.
Media Credit: Kenji Explains Filed Under: AI, Guides
Latest Geeky Gadgets Deals
Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Try Our AI Features
Explore what Daily8 AI can do for you:
Comments
No comments yet...
Related Articles
Geeky Gadgets
4 hours ago
- Geeky Gadgets
Supercharge Your Power BI Excel Dashboards Using Measures and Calculated Columns
Have you ever felt overwhelmed by the sheer volume of data in your Power BI reports, unsure how to make sense of it all? The key to unlocking the full potential of your data lies in understanding how to use measures and calculated columns effectively. These two tools aren't just technical jargon—they're the backbone of creating dynamic, interactive, and efficient reports. Yet, many users struggle to grasp when to use one over the other, leading to bloated models or underperforming dashboards. In this step-by-step overview, Simon Sez IT demystifies these concepts, showing you how to transform raw data into actionable insights with precision and clarity. By the end of this guide, you'll uncover how measures enable real-time calculations that adapt seamlessly to user interactions, while calculated columns offer a static yet powerful way to enrich your datasets. You'll also explore practical examples, best practices, and potential pitfalls to avoid, making sure your reports are both insightful and optimized for performance. Whether you're calculating profit margins or crafting dynamic KPIs, this tutorial will equip you with the tools to make informed decisions and elevate your Power BI skills. Let's explore how these techniques can transform the way you approach data analysis. Measures vs Calculated Columns Measures: Dynamic Calculations for Real-Time Insights Measures are powerful tools in Power BI, designed to perform dynamic calculations that adapt to user interactions, such as filters and slicers. They calculate results in real time, making them ideal for aggregations like totals, averages, percentages, or other metrics that depend on the context of the data being viewed. This adaptability allows measures to provide tailored insights based on the specific criteria selected by the user. For instance, if you need to calculate total sales for a specific region or time period, a measure will dynamically adjust its results based on the filters applied. Measures are written using DAX (Data Analysis Expressions), a formula language specifically designed for Power BI. By using measures, you can create interactive reports that respond instantly to user inputs, significantly enhancing the analytical experience. Calculated Columns: Static Calculations at the Row Level Calculated columns, in contrast to measures, perform static calculations at the row level within a table. These columns are created by adding new fields to your dataset, with values derived from existing data. Once calculated, the values in a calculated column remain fixed and do not change dynamically with user interactions or filters. Calculated columns are particularly useful when you need to create new fields for analysis. For example, you might calculate a profit margin by subtracting costs from revenue for each row in your dataset. However, it's important to note that calculated columns can increase the size of your data model, which may impact performance. While they are valuable for certain scenarios, their use should be carefully considered to avoid unnecessary strain on your data model. How to Use Measures and Calculated Columns in Power BI for Better Reports Watch this video on YouTube. Here are more guides from our previous articles and guides related to Power BI measures that you may find helpful. Key Differences Between Measures and Calculated Columns To effectively use measures and calculated columns, it's crucial to understand their key differences. These distinctions will guide you in selecting the right tool for your specific needs: Functionality: Measures are dynamic and adapt to user interactions, while calculated columns are static and operate at the row level. Measures are dynamic and adapt to user interactions, while calculated columns are static and operate at the row level. Performance: Measures are generally more efficient as they do not increase the size of your data model. Calculated columns, on the other hand, can consume additional memory and potentially slow down performance. Measures are generally more efficient as they do not increase the size of your data model. Calculated columns, on the other hand, can consume additional memory and potentially slow down performance. Use Cases: Measures are best suited for aggregations and calculations that depend on filters or slicers. Calculated columns are ideal for creating new fields that are required for further analysis or categorization. By understanding these differences, you can ensure that your Power BI reports are both functional and optimized for performance. Step-by-Step Guide to Creating Measures and Calculated Columns Creating measures and calculated columns in Power BI is a straightforward process. Follow these steps to incorporate them into your workflow: Creating a Measure: Navigate to the 'Modeling' tab in Power BI Desktop. Select 'New Measure' and enter a DAX formula to define the calculation. Test the measure by applying filters or slicers to your report to observe how it dynamically adjusts. Creating a Calculated Column: Select the relevant table in the Fields pane. Click 'New Column' and write a DAX formula to define the calculation. The new column will appear in your dataset and can be used in visualizations or further analysis. These steps provide a clear foundation for creating measures and calculated columns, allowing you to build more dynamic and insightful Power BI reports. Practical Applications and Best Practices To maximize the effectiveness of measures and calculated columns, consider the following practical applications and best practices: Enhancing Data Insights: Use measures to create dynamic KPIs, such as year-over-year growth, profit margins, or customer retention rates, that respond to user inputs in real time. Use measures to create dynamic KPIs, such as year-over-year growth, profit margins, or customer retention rates, that respond to user inputs in real time. Optimizing Performance: Minimize the use of calculated columns to prevent bloating your data model. Whenever possible, rely on measures for calculations to maintain efficiency and performance. Minimize the use of calculated columns to prevent bloating your data model. Whenever possible, rely on measures for calculations to maintain efficiency and performance. Organizing Your Data Model: Group and categorize measures and calculated columns logically within your data model. This organization simplifies report maintenance and ensures scalability as your analysis grows more complex. Group and categorize measures and calculated columns logically within your data model. This organization simplifies report maintenance and ensures scalability as your analysis grows more complex. Testing and Validation: Regularly test your measures and calculated columns to ensure accuracy and alignment with your analysis objectives. This step is critical for maintaining the reliability of your reports. By applying these best practices, you can create Power BI reports that are both insightful and efficient, empowering you to make data-driven decisions with confidence. Media Credit: Simon Sez IT Filed Under: Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
Reuters
6 hours ago
- Reuters
AI ‘vibe coding' startups burst onto scene with sky-high valuations
NEW YORK, NY, June 3 (Reuters) - Two years after the launch of ChatGPT, return on investment in generative AI has been elusive, but one area stands out: software development. So-called code generation or 'code-gen' startups are commanding sky-high valuations as corporate boardrooms look to use AI to aid, and sometimes to replace, expensive human software engineers. Cursor, a code generation startup based in San Francisco that can suggest and complete lines of code and write whole sections of code autonomously, raised $900 million at a $10 billion valuation in May from a who's who list of tech investors, including Thrive Capital, Andreessen Horowitz and Accel. Windsurf, a Mountain View-based startup behind the popular AI coding tool Codeium, attracted the attention of ChatGPT maker OpenAI, which is now in talks to acquire the company for $3 billion, sources familiar with the matter told Reuters. Its tool is known for translating plain English commands into code, sometimes called 'vibe coding,' which allows people with no knowledge of computer languages to write software. OpenAI and Windsurf declined to comment on the acquisition. 'AI has automated all the repetitive, tedious work,' said Scott Wu, CEO of code gen startup Cognition. 'The software engineer's role has already changed dramatically. It's not about memorizing esoteric syntax anymore.' Founders of code-gen startups and their investors believe they are in a land grab situation, with a shrinking window to gain a critical mass of users and establish their AI coding tool as the industry standard. But because most are built on AI foundation models developed elsewhere, such as OpenAI, Anthropic, or DeepSeek, their costs per query are also growing, and none are yet profitable. They're also at risk of being disrupted by Google, Microsoft and OpenAI, which all announced new code-gen products in May, and Anthropic is also working on one as well, two sources familiar with the matter told Reuters. The rapid growth of these startups is coming despite competing on big tech's home turf. Microsoft's GitHub Copilot, launched in 2021 and considered code-gen's dominant player, grew to over $500 million in revenue last year, according to a source familiar with the matter. Microsoft declined to comment on GitHub Copilot's revenue. On Microsoft's earnings call in April, the company said the product has over 15 million users. As AI revolutionizes the industry, many jobs - particularly entry-level coding positions that are more basic and involve repetition - may be eliminated. Signalfire, a VC firm that tracks tech hiring, found that new hires with less than a year of experience fell 24% in 2024, opens new tab, a drop it attributes to tasks once assigned to entry-level software engineers are now being fulfilled in part with AI. Google's CEO also said in April that 'well over 30%' of Google's code is now AI-generated, and Amazon CEO Andy Jassy said, opens new tab last year the company had saved 'the equivalent of 4,500 developer-years' by using AI. Google and Amazon declined to comment. In May, Microsoft CEO Satya Nadella said at a conference that approximately 20 to 30% of their code is now AI-generated. The same month, the company announced layoffs of 6,000 workers globally, with over 40% of those being software developers in Microsoft's home state, Washington. 'We're focused on creating AI that empowers developers to be more productive, creative, and save time,' a Microsoft spokesperson said. 'This means some roles will change with the revolution of AI, but human intelligence remains at the center of the software development life cycle.' MOUNTING LOSSES Some 'vibe-coding' platforms already boast substantial annualized revenues. Cursor, with just 60 employees, went from zero to $100 million in recurring revenue by January 2025, less than two years since its launch. Windsurf, founded in 2021, launched its code generation product in November 2024 and is already bringing in $50 million in annualized revenue, according to a source familiar with the company. But both startups operate with negative gross margins, meaning they spend more than they make, according to four investor sources familiar with their operations. 'The prices people are paying for coding assistants are going to get more expensive,' Quinn Slack, CEO at coding startup Sourcegraph, told Reuters. To make the higher cost an easier pill to swallow for customers, Sourcegraph is now offering a drop-down menu to let users choose which models they want to work with, from open source models such as DeepSeek to the most advanced reasoning models from Anthropic and OpenAI so they can opt for cheaper models for basic questions. Both Cursor and Windsurf are led by recent MIT graduates in their twenties, and exemplify the gold rush era of the AI startup scene. 'I haven't seen people working this hard since the first Internet boom,' said Martin Casado, a general partner at Andreessen Horowitz, an investor in Anysphere, the company behind Cursor. What's less clear is whether the dozen or so code-gen companies will be able to hang on to their customers as big tech moves in. 'In many cases, it's less about who's got the best technology -- it's about who is going to make the best use of that technology, and who's going to be able to sell their products better than others,' said Scott Raney, managing director at Redpoint Ventures, whose firm invested in Sourcegraph and Poolside, a software development startup that's building its own AI foundation model. Most of the AI coding startups currently rely on the Claude AI model from Anthropic, which crossed $3 billion in annualized revenue in May in part due to fees paid by code-gen companies. But some startups are attempting to build their own models. In May, Windsurf announced its first in-house AI models that are optimized for software engineering in a bid to control the user experience. Cursor has also hired a team of researchers to pre-train its own large frontier-level models, which could enable the company to not have to pay foundation model companies so much money, according to two sources familiar with the matter. Startups looking to train their own AI coding models face an uphill battle as it could easily cost millions to buy or rent the computing capacity needed to train a large language model. Replit earlier dropped plans to train its own model. Poolside, which has raised more than $600 million to make a coding-specific model, has announced a partnership with Amazon Web Services and is testing with customers, but hasn't made any product generally available yet. Another code gen startup Magic Dev, which raised nearly $500 million since 2023, told investors a frontier-level coding model was coming in summer 2024 but hasn't yet launched a product. Poolside declined to comment. Magic Dev did not respond to a request for comment.
Geeky Gadgets
9 hours ago
- Geeky Gadgets
27 Essential Excel Shortcuts to improve productivity
Have you ever found yourself drowning in a sea of spreadsheets, endlessly clicking through menus and tabs, trying to make sense of your data? You're not alone. The average Excel user spends nearly 40% of their time navigating and performing repetitive tasks—time that could be better spent analyzing insights or completing other critical work. But what if there was a way to cut that time in half? Mastering a few essential Excel shortcuts can transform how you work, turning hours of tedious clicking into streamlined, efficient workflows. With just a few keystrokes, you can unlock Excel's full potential and reclaim valuable time in your day. In this feature, Excel Campus takes you through 27 essential Excel shortcuts designed to boost your productivity and simplify your workflow. From navigating massive datasets with precision to editing formulas and automating repetitive tasks, these shortcuts are more than just time-savers—they're tools that empower you to work smarter, not harder. Whether you're a beginner eager to learn the basics or a seasoned pro looking to fine-tune your skills, this guide offers something for everyone. Ready to uncover the hidden efficiencies that Excel has to offer? Let's explore how these shortcuts can transform the way you work with data. Essential Excel Shortcuts Guide Ribbon and Screen Management Keeping your workspace organized is crucial for maintaining productivity. These shortcuts allow you to manage your screen layout effectively and reduce distractions: Hide or show the ribbon: Press Ctrl + F1 to toggle the ribbon, creating more space for your data. Press to toggle the ribbon, creating more space for your data. Full-screen mode: Use Ctrl + Shift + F1 to remove interface elements and focus entirely on your work. Use to remove interface elements and focus entirely on your work. Access the Quick Access Toolbar: Press Alt to highlight the Quick Access Toolbar, allowing you to execute commands without using the mouse. Editing and Formulas Editing formulas and cell content can be time-consuming, but these shortcuts simplify the process and improve accuracy: Edit a cell or view its formula: Press F2 to directly edit a cell or examine its formula. Press to directly edit a cell or examine its formula. Edit in the formula bar: Use Ctrl + F2 to make changes in the formula bar. Use to make changes in the formula bar. Toggle references: Press F4 to switch between absolute, relative, and mixed references in formulas. Press to switch between absolute, relative, and mixed references in formulas. Manual calculation: Use F9 to calculate the workbook or evaluate specific formula components. Use to calculate the workbook or evaluate specific formula components. Insert functions: Press Shift + F3 to open the Insert Function dialog box and quickly find the formula you need. 27 Essential Excel Shortcuts For Faster Editing Watch this video on YouTube. Browse through more resources below from our in-depth content covering more areas on Excel functions. Navigation and Selection Efficient navigation is essential when working with large datasets. These shortcuts help you move through your workbook and select data with precision: Go to a specific range: Press F5 or Ctrl + G to open the 'Go To' menu and jump to named ranges or tables. Press or to open the 'Go To' menu and jump to named ranges or tables. Cycle through workbook areas: Use F6 to shift focus between different sections of the workbook, such as the worksheet, ribbon, and task pane. Use to shift focus between different sections of the workbook, such as the worksheet, ribbon, and task pane. Switch between workbooks: Press Ctrl + F6 to toggle between open workbooks. Press to toggle between open workbooks. Select ranges: Activate extend selection mode with F8 for precise range selection. Activate extend selection mode with for precise range selection. Navigate to the last cell: Use Ctrl + End to jump to the last cell containing data in your worksheet. Data Management Managing data efficiently is a cornerstone of productivity in Excel. These shortcuts simplify common data-related tasks: Open Name Manager: Use Ctrl + F3 to manage named ranges and tables. Use to manage named ranges and tables. Refresh data: Press Alt + F5 to update a selected Pivot Table or query. For all Pivot Tables and queries, use Ctrl + Alt + F5 . Press to update a selected Pivot Table or query. For all Pivot Tables and queries, use . Filter data: Use Ctrl + Shift + L to apply or remove filters from your data range. Use to apply or remove filters from your data range. Sort data: Press Alt + D + S to open the Sort dialog box and organize your data efficiently. Chart and Visualization Creating visual representations of data is a powerful way to analyze and communicate information. These shortcuts make it easier to generate and manage charts: Create a chart: Select your data and press Alt + F1 to instantly generate a chart on the current worksheet. Select your data and press to instantly generate a chart on the current worksheet. Create a chart on a new sheet: Use F11 to create a chart on a separate worksheet for better organization. Use to create a chart on a separate worksheet for better organization. Pivot Chart creation: If working with Pivot Tables, the same shortcut ( Alt + F1 ) creates a Pivot Chart, helping you analyze trends quickly. Macros and Automation Automation can save significant time on repetitive tasks. These shortcuts help you manage and create macros efficiently: Open the Macro window: Press Alt + F8 to view, run, or manage macros. Press to view, run, or manage macros. Access the VBA editor: Use Alt + F11 to create or edit custom macros for advanced automation. Use to create or edit custom macros for advanced automation. Record a macro: Press Alt + T + M + R to start recording a macro, allowing you to automate repetitive tasks. File Management Efficient file management ensures that your work is saved and organized properly. These shortcuts simplify common file-related tasks: Save As: Press F12 to open the 'Save As' window and save your file with a new name or location. Press to open the 'Save As' window and save your file with a new name or location. Insert a new worksheet: Use Shift + F11 to quickly add a new worksheet to your workbook. Use to quickly add a new worksheet to your workbook. Close the workbook: Press Ctrl + W to close the current workbook without exiting Excel. Additional Tips To maximize the benefits of these shortcuts, consider the following strategies: Enable the function lock on laptops with compact keyboards to access function key shortcuts more easily. Explore VBA (Visual Basic for Applications) to create custom solutions tailored to your workflow and automate complex tasks. Practice regularly to build muscle memory and increase your proficiency with these shortcuts. Download a comprehensive Excel shortcuts guide for quick reference and continued learning. By incorporating these shortcuts into your daily routine, you can significantly enhance your productivity in Excel. Whether you're navigating large datasets, editing complex formulas, or automating repetitive tasks, these tools empower you to work smarter and more efficiently. Media Credit: Excel Campus – Jon Filed Under: Guides Latest Geeky Gadgets Deals Disclosure: Some of our articles include affiliate links. If you buy something through one of these links, Geeky Gadgets may earn an affiliate commission. Learn about our Disclosure Policy.
