Data reporting has long been a cornerstone of running businesses. Whether filing earnings with the SEC or doing strategic planning, organizations rely on data reports to understand the state of their business, customers, and products.
In our evermore digital world, the demand and requirements for data reporting have dramatically changed . Using data to stay ahead of competitors, tap new opportunities, and avoid unnecessary risk can be the difference between success and failure, driving massive investments in the modern data stack.
Despite this need, data leaders still report abysmal adoption of analytics projects, fueled by dead, static reports and dashboards that keep insights locked in the past and decisions about the future uncertain. Luckily, the evolution of data reporting, including ad hoc reporting that let’s individuals ask and answer their own questions in real time, is creating new means for leaders and businesses to turn reports into impact. That's why it's important to understand not just what data reporting is but also which best practices need to be followed when undertaking a data reporting project.
In this post, we'll explore both topics - defining what data reporting is at its core as well as going over some of the top steps that should be taken in order to secure accurate results from your reports.
Data reporting is the process of collecting and presenting data in a structured format to facilitate data-driven decision making. The goal of data reporting is to make data easily understandable and accessible to stakeholders, such as managers, executives, and clients. This involves selecting and analyzing relevant data, and presenting the results in a clear, concise, and visually appealing way. Data reporting is often part of a business intelligence program, and includes everything from pixel perfect reports for regulatory bodies, as well as ad hoc reports generated through self-service analytics as business users have questions.
Effective data reporting is essential for businesses to be able to share the status of various parts of their organization and make informed decisions. By providing stakeholders with accurate, relevant, and timely information, backed by data,, they can identify trends, patterns, and insights that can help them understand their business better. This can lead to improvements in areas such as operations, customer service, marketing, and sales, which can ultimately drive business growth.
When building a report, it’s easy to slip into the thinking that you need to include every potential piece of information that could possibly be of value. One of the most important principles of effective data reporting is to keep it simple. Complex reports that are difficult to read and understand can be counterproductive, as they may obscure key insights and lead to confusion or inaction. To avoid this then creating a data report, focus on the key metrics that matter most to your business. Don't try to include every piece of data that you have available, as this can lead to information overload. Instead, focus on the metrics that are most relevant to your business objectives and provide a clear picture of performance. By using a data analytics tool like ThoughtSpot, you can also continue to drill into your report if you have follow up questions, reducing the information overload without limiting your user’s ability to get to the answer they want.
Data visualization allows you to convey complex information in a way that is easy to understand and interpret. By presenting data in charts, graphs, and other visual formats, you can quickly unearth meaningful insights that might be missed in a table of numbers.
When choosing a data visualization tool, consider the types of data you'll be working with and the audience you'll be presenting to. Different visualization methods may be more appropriate for different types of data, and some tools may be better suited to certain audiences. For example, if you are building a report that many domain experts or business users will use, consider an interactive data visualization tool that allows your users to click into a specific chart or graph, tailor it to their needs, without requiring extensive technical resources.
When presenting data, it's essential to provide a clear understanding of the context in which the data was collected and the meaning behind the numbers. For example, if you're reporting on website traffic, it's important to note whether the data includes mobile traffic or only desktop traffic, as this can have a significant impact on the insights gained. This can help to ensure that the insights gained from the data are accurate and actionable. Generative AI tools like Sage take this even further, using large language models like GPT to create a natural language narrative to explain insights, meaning everyone is on the same page.
To ensure that your reports have reliable data and are accurate, it's essential to use consistent data quality metrics, data sources, and reporting periods. Implementing or leveraging a cloud data platform as a single source of truth can be very effective.
In creating this reliable, clean data, you can avoid confusion and ensure all stakeholders are working from the same version of the data instead of arguing about whose data is more correct, accurate, or up to date.
When creating data reports, establish a clear process to follow for consistency and ensure that all stakeholders are aware of them. This can help to prevent misunderstandings and ensure that everyone is working from the same set of assumptions.
Effective data reporting is an essential aspect of any business analytics program, and helps build a truly data-driven organization. Here are five steps you can follow to create an effective data report:
Like all good things, start at the very beginning: why are you creating your report at all. This involves identifying the purpose of your report, determining the audience of your report, and establishing key performance indicators (KPIs) that will be used to measure success. You may need to create different reports for different stakeholders, such as executives, managers, or customers, or for different use cases. For example, you may want to forecast sales for the next quarter, monitor customer satisfaction, or see how you can optimize inventory.
Once your goals are clear, you’re ready to begin preparing the data foundation. This involves identifying relevant data sources, data cleaning, and preparing the data. This may involve removing duplicates, correcting errors, or formatting the data to ensure consistency. The data sources you use will depend on the specific goals and objectives of your report. From there, you’re ready to start analyzing the data to draw conclusions and insights.
Seeing your data can be a powerful way to identify insights. To determine the type of visualization to use, consider the type of data you have and the message you want to convey. Some common types of visualizations include histograms, bar charts, line charts, pie charts, scatterplots, and maps. Each type of visualization has its own strengths and weaknesses, so it is important to choose the right type for your data. Creating effective data visualizations involves more than just choosing the right type of chart or graph. It is important to consider the design and layout of your visualization to ensure that it is easy to read and understand. Consider following these data visualization design tips when you get to this step.
Organizing your report effectively can help ensure that your audience can easily find the information they need and understand the key takeaways from your data. This is the perfect time to make sure you’re considering the purpose and audience for your report so the most relevant, impactful information is easily accessible.
Armed with this information and the insights you want to convey, you can create an outline for your report that can help you organize your thoughts and ensure that your report is structured logically. Your outline should include key sections, such as an executive summary, introduction, data analysis, and conclusion. The executive summary should be a brief overview of your report, highlighting the key takeaways and conclusions. It should be written in a way that is accessible to a non-technical audience and should provide a clear and concise summary of your findings.
Review your report carefully, check for errors, inconsistencies, and gaps in your analysis. Consider the tone and style of your report, ensuring that it is written in a way that is accessible and engaging to your audience. After you do this, it is important to get feedback from stakeholders who will be reviewing and using the report. This can include colleagues, supervisors, clients, or other relevant parties. Provide specific questions or prompts for feedback, and ask for feedback on both the content and presentation of the report. Be open to suggestions and be willing to make changes based on feedback.
For example, many executives and managers want to dig deeper into a given report in real-time, while they’re in meetings. By making your report interactive through AI-Powered Analytics, stakeholders can explore your report without having to ask the data team to re-engage.
Once you have received feedback and made any necessary revisions, it is time to finalize and publish your report. After publishing your report, it is important to track how it is received and used. This can help you assess the effectiveness of your report and improve future versions.
Data reporting is immensely important in making business decisions and ensuring the success of an organization. However, not all data reporting is made equal. Organizations need data reporting complete with interactive visualizations and intuitive design if they want to reap the rewards of data-driven decision making. Whether you are starting a business or growing one, following the practices we outlined throughout this post will help you create reports that offer an accurate and complete picture of your organization's data without stymieing you with stale insights in static, dead dashboards.
Now it’s time to put your newfound knowledge into practice and empower everyone to build data reports. Sign up for a ThoughtSpot free trial today to see how anyone can use data reporting to gain deeper insights into your company’s performance. You don’t have to be a data expert to get started – ThoughtSpot allows even beginners to leverage the power of AI Analytics without requiring extensive tech skills or background experience.