Here's how you can write clear and informative data warehousing reports.

?? Think of your report as a GPS for decision-makers. If your audience is technical, zero in on specifics like ETL processes and data integrity. If you're talking to execs, spotlight metrics like cost savings and user adoption rates. Tailor every section to what matters most to them. This targeted approach not only makes your report more relevant but also ensures that the insights you provide are actionable and aligned with the organization's strategic goals. Tools like Power BI or Tableau can transform these insights into compelling visuals that drive home your points. Sources: Power BI Visualization Tableau Data Reporting

?? Imagine your report as a finely curated art exhibit. Not every piece of data deserves a spot on the wall. Focus on what will truly tell the story your audience needs to hear. Use SQL queries to sift through your data warehouse and bring forward only the most relevant data points. This precision prevents drowning your audience in data and highlights the insights that matter most. Tools like Hadoop or Apache Spark can help manage and filter large datasets efficiently, ensuring that your report remains sharp and impactful. Sources: Hadoop Data Management Apache Spark Data Processing

some of the best practices while creating visual aids 1. Purpose-Driven: Ensure each visual aid has a clear purpose and adds value to the report. 2. Simplicity: Avoid clutter and keep visuals simple for easy understanding. 3. Consistency: Use consistent colors, fonts, and styles across all visuals. 4. Clarity: Label charts and graphs clearly, and include legends where necessary. 5. Interactivity: Where possible, use interactive visuals to allow deeper exploration of data.

4 Clear Language The language you use in your report should be as clear and concise as possible. Avoid jargon and technical terms unless they are widely understood by your audience. If you must use specialized language, provide definitions to ensure comprehension. Clear language helps to bridge the gap between data experts and business stakeholders, making your report a tool for informed decision-making rather than a source of confusion.

?? Think of your report as a sculptor's masterpiece. The first draft is just the rough shape. Iterate, refine, and polish. Start by evaluating if your report meets its goals and if the data is presented clearly. Ask yourself if non-technical stakeholders can grasp the key insights. Don't be afraid to seek feedback from peers or potential users. Tools like Tableau or Power BI can help visualize and refine your data presentation. This iterative process ensures your final report is not just accurate, but also clear and compelling. Sources: Tableau Power BI

Separate the data will use from its presentation because if you need to modify some units, scales or time frames; you can do it faster.

They are known as BI reports, or analytics. They contain business trends and opportunities, reflecting how the business went in the past, and how it could grow in the future. The best forms of such reports are interactive, where business users can change the parameters such as the month, the business line and the client group. The most valuable analytics however is not the one that reflects the past, but the one that predicts the future. This kinds of analytics are not BI, they are AI. But they are formulated from a data warehouse, so I suppose we could call them data warehouse reports, be it not a popular term as it may.