How do you define data reporting requirements?

1. Know what is the ultimate goal of your project and have the complete context about your data lifecycle. 2. Understand your data sources and its schema. 3. Ensure that you are doing analytics on the Gold tables for precise insights. There might be additional transformations that you need to make, but these should not be as complex as the initial steps. You can leverage your reporting tool for these needs ideally. 4. Know your audience. A team lead wants to see different metrics and visualizations when compared to a business executive for the same project. 5. Handpick the visualizations tailored to your audience and ensure that they demonstrate your requirements. 6. Evaluate and Optimize. 7. Create a beautiful story from this and present.

Define data reporting requirements by engaging with stakeholders to determine the specific metrics and insights they need, how often reports should be generated, which data sources are relevant, and in what format information should be presented. Document these requirements thoroughly, specifying user access levels and ensuring alignment with overall business objectives for effective and meaningful reporting

Compreender os objetivos e requisitos do negócio é fundamental para identificar as principais perguntas, problemas ou oportunidades de negócios que o relatório abordará. Entender as fontes de dados, os padr?es de qualidade, as políticas de acesso aos dados, a seguran?a e a privacidade s?o requisitos essenciais visando este objetivo.

-->Purpose & Goals: What's the report for? What questions will it answer? -->Audience: Who needs the info? Tailor complexity and language accordingly. -->Data Sources: Where's the info coming from? Ensure quality and accessibility. -->Metrics & KPIs: Choose data points that align with goals and track progress. -->Format & Structure: Decide on presentation style (charts, tables) and information organization. -->Frequency & Delivery: How often is it needed, and how will it be delivered?

1.Identify the key questions that the report needs to answer. This could involve problem-solving, opportunity identification, or decision-making needs. Ensure that these questions are aligned with the broader business strategy and goals. 2.Identify all stakeholders involved and understand their interests and requirements. Analyze how the report will impact different departments or roles within the organization.

Are you working on Data related any technology you must know that point what is data source and when it come and what's our work on the data and where to summit our work then how to help my company and stakeholders doing this work on the data for example if you're working on Data Engineer your upstream was Data base and downstream was data science depending upon projects and you're a Data Engineer or any else in data field of work but you can't knowing this information just simply working they not help career journey because we are living on competitive market not a corporate, so keep updating your self day to day life.

Specify the data sources from which information will be gathered. Define the methods and frequency of data collection. Specify the format of the reports (e.g., tables, charts, dashboards). Define the layout, design, and any specific visual elements to be included.

This is the most exciting part of making reports. You need to know the basics of data modeling and SQL first. Then, it's time to really get to know your data - figuring out which fields matter for what you need, understanding the different tables, and how to connect them without messing up and making duplicates. It's all about getting into the details of your data and setting everything up right for your reports.

Data Sources: Identify and document the sources of data. This could include databases, APIs, flat files, or any other repositories where relevant data is stored. Data Quality and Consistency: Assess the quality and consistency of the data sources. Identify any data cleansing or transformation requirements needed to ensure accuracy in reporting. Technical Specifications: Document technical specifications, such as data formats, structures, and any data processing requirements. This information is essential for data extraction and transformation processes.

Acrescento que além das fontes de dados, os padr?es de qualidade, as políticas de acesso aos dados, a seguran?a e a privacidade s?o requisitos essenciais e também devem ser especificados.

Identify the specific data elements you need to include in your report, such as sales, customer demographics, or website traffic. Define metrics or KPIs (Key Performance Indicators) that are important to analyze, make decisions, and track business performance.

Clear definition ensures that the information presented aligns with the business goals and provides meaningful insights. Also, understanding how these elements will be calculated and manipulated is essential for creating a robust data model and logic. All these are needed for an effective and insightful report.

Key Performance Indicators (KPIs): Define the specific metrics and KPIs that will be included in the reports. These should directly align with the business objectives and provide actionable insights. Granularity and Aggregation: Determine the level of granularity required for the data. Understand whether the reports should display detailed data or aggregated summaries based on the audience's needs. Calculations and Formulas: Specify any calculations or formulas required for deriving specific metrics. Clearly document how each metric will be calculated to ensure consistency and accuracy.

1. Understand Business Requirements: Stakeholder Discussions: Engage in discussions with stakeholders to understand the specific business questions or decisions the reports are intended to address. User Personas: Consider the needs of different user personas and departments. Tailor the data elements and metrics to align with their specific requirements. 2. Identify Key Performance Indicators (KPIs): Business Goals: Align data elements and metrics with overall business goals. Identify KPIs that directly measure the success of the business strategy. Performance Indicators: Define metrics that reflect the performance of critical business processes, products, or services.

Understand Reporting Objectives: Review the objectives of the reporting project to understand what insights or outcomes are desired. This will help in determining which data elements and metrics are most relevant. Identify Key Data Elements: Start by identifying the core data elements or dimensions that are essential for the analysis. These may include attributes such as time, location, product/service, customer demographics, etc. Consider both qualitative (e.g., categories, descriptions) and quantitative (e.g., numerical values) data elements. Select Metrics and Measures: Determine the metrics and measures that will be used to quantify and evaluate performance, trends, or outcomes related to the reporting objectives.

Choosing a report format (tables, graphs, dashboards) that best meets the requirements and tastes of the target audience. Choosing the best visualization tools (line graphs, pie charts, and bar charts) to convey the facts effectively.

Report Structure: Define the overall structure of the reports, including sections, tables, charts, and any other visual elements. Consider the logical flow of information. Visualization Techniques: Choose appropriate visualization techniques for presenting different types of data. Consider using charts, graphs, tables, and other visual aids to enhance data comprehension. User Interface Considerations: Consider the user interface elements, such as filters, drill-down options, or interactive features, to enhance the user experience and provide flexibility.

Some points help me when i design reports: ?? Group all charts inside specificed sections to navigate easier. ?? Only use internal widget to give more explain about main graphic. ?? Use business terms in all text of report. ?? If apply; add definition of metrics or concepts in report like helper points. ?? try to use color what help to colorblind people to understand the reports.

Don't just throw numbers on a screen! Craft visuals that tell a clear and compelling story: Choose the right chart type: Lines for trends, bars for comparisons, maps for geographic data, etc. Color palettes: Use colors effectively to highlight key data points and avoid visual clutter. Layout and organization: Prioritize readability and logical flow of information. Interactive elements: Consider adding interactivity for deeper exploration and customization. Think of your audience and choose visualizations that resonate with them.

"Just because you can does not mean you should." Understanding the right visualization and implementing the right layout is critical. For example, intentionality with the use of color greatly aids the user in understanding the data; colors like red and orange are used to alert a user, where as green is often used to communicate something positive. By contrast, using a pie chart for non-proportional data will add little value to your report and prove ineffective in communicating the important information. A great resource is a book titled "The Big Book of Dashboards" which will cover most of what a report developer needs to know about how to deliver exceptional reporting products.

- Create reports on a daily, weekly, or monthly basis to meet business requirements and fit with decision-making cycles. - Determine when reports should be delivered to ensure stakeholders have access to information on time. - Identify the audience (Executives, Managers, Analysts) who will consume the reports and tailor the content and granularity to meet their needs. - Decide how the reports will be distributed (email, social media, print, etc.) and ensure they are easily accessible to the target audience.

1. Choose Data Delivery Methods: Scheduled Reports: Set up automated schedules for report delivery, ensuring that stakeholders receive timely updates without manual intervention. Email Notifications: Consider sending email notifications or alerts to inform users when new reports are available or when specific thresholds are met. Dashboard Access: Provide access to dashboards or reporting platforms where users can interact with and explore the data in real-time. 2. Define Data Refresh Frequencies: Real-Time Updates: Determine if real-time data updates are required for the reports, especially for critical metrics that demand immediate attention. Scheduled Refresh: Specify the frequency of scheduled data refreshes.

How will your data report be delivered and kept fresh? Define the logistics: Frequency: Daily, weekly, monthly, or customized reports based on your needs. Delivery format: Email, online dashboards, PDFs, or integrated into other systems. Data refresh schedule: How often will the data be updated to reflect the latest information? Access control: Who can access the reports and what level of detail do they need? Ensure easy access to accurate and up-to-date data for informed decision-making.

Delivery Frequency: Determine how often the reports will be generated and delivered. This could range from real-time reporting to daily, weekly, or monthly schedules. Distribution Channels: Define the channels through which reports will be distributed. This could include email, dashboards, web portals, or other delivery mechanisms. Data Refresh and Update: Specify how often data will be refreshed or updated to ensure that the reports reflect the most current information.

Define Data Delivery Channels: Determine the channels through which the report will be delivered to the intended audience. This could include email distribution, a dedicated reporting portal or dashboard, printed reports, or presentations during meetings. Consider the frequency and timing of report delivery to align with the needs and preferences of the audience. Select Data Visualization Tools: Choose the appropriate tools or software for creating and delivering data visualizations. This may include business intelligence (BI) platforms, data visualization software, or custom-built reporting solutions. Consider factors such as ease of use, compatibility with data sources, scalability, and support for interactive or dynamic visualizations.

I believe the success of a data reporting system depends on user acceptance. Involving stakeholders in the validation process allows them to see and interact with prototypes or sample reports. Their feedback during user acceptance testing ensures that the final product aligns with their expectations and is user-friendly.

Regularly review and update data reporting requirements to adapt to changing business needs. Gather feedback from stakeholders to improve the effectiveness of the reports.

Get feedback and tweak your recipe! Validate your data reporting requirements with key stakeholders: Gather feedback: Get input from users on the report's usefulness, clarity, and accessibility. Test and refine: Run pilot reports and adjust visualizations, metrics, and layout based on feedback. Document the final requirements: Create a clear and concise document outlining the agreed-upon specifications. Continuous improvement ensures your data reports remain relevant and impactful.

I think that the validation process of data during the project should be interactive. Although validation with dashboards for stakeholders is important, during the process, small milestones are necessary to give confidence to the team and the business. Prototypes once delivery is validated will be part of the process and are extremely important and inexpensive. Roundtables of feedback with future users also help to validate that the deliverables are in line with the requirements. In the end, we can say that validation takes place throughout the data project.

Finding where the data comes from for reports and making sure it's reliable, consistent, and accurate. Setting rules for handling data to keep it accurate and make sure the information shown is trustworthy.

Once your delivery has been validated and the project completed, we can consider other points that make up the post-delivery process, such as: - Data and access security; - Delivery performance and whether it meets the SLA; - Reviewing requirements and adjusting the sources and delivery of reports; - Analyzing pipeline performance; - Documenting lessons learned; - Creating the organization's knowledge assets to facilitate new projects; - Data reliability.

Data Security: Ensure data privacy and compliance with relevant regulations. Technology and Automation: Explore tools and software for automated data collection and report generation. Cost-Effectiveness: Balance the cost of data reporting with the value it delivers to the business. Remember, data reporting is not a one-time task. It's an ongoing process that requires continuous refinement to ensure its effectiveness and value.

1. Accessibility is always overlooked. Extremely small fonts and poor use of color puts those with poorer vision or colorblindness at a disadvantage. Knowing your audience and accounting for these factors goes a long way. 2. Handle potentially sensitive information with care. Ensure permissions are properly applied in accordance with the principle of least privilege and remove any unnecessary data from the dataset. While a single report may not be inherently sensitive, consider what underlying data and other reports that a user may have access to. The aggregation of information across multiple sources can sometimes be easily stitched together and used for nefarious purposes. As always, ensure compliance with all relevant policies and laws.

Data reporting requirements should be developed through a collaborative effort involving data analysts, data scientists, business stakeholders, and end-users. This cross-functional approach ensures that the report aligns with business objectives, technical feasibility, and audience needs.