Ad hoc reporting tools enable you to easily build custom reports without needing help from IT or writing any code. At any given time, you can use ad hoc reporting tools to create and share reports that answer your specific questions using live data from your systems. This saves you time and helps you make informed decisions faster.
At Vidi Corp, we’ve helped over 600 clients maximise the value of their data using ad hoc reporting tools. Drawing on our expertise, we’ve prepared this detailed guide to help you do the same.
Ad hoc reporting tools are self-service business intelligence tools that let you create reports at any given time without writing code or waiting for IT.
“Ad hoc” means “as needed,” and that’s exactly what these tools give you: the ability to answer specific questions in the moment using live data from your systems.
With ad hoc reporting tools, you don’t have to wait days for someone else to build a report for you. You can answer business questions as they arise using live data and a simple drag-and-drop interface: no more outdated reports or limited templates.
Plus, since these tools are for non-technical users, anyone on your team can use them, not just analysts or IT staff. This breaks down data silos and lets every department make better, faster decisions.
Ad hoc reporting tools are simple, flexible, and for everyday business decisions because they are:
You can build reports by clicking, dragging, and selecting from menus without needing any special skills or technical knowledge.
Data updates automatically, so every report you create reflects what’s happening in your business at present.
You can adjust dashboards to focus on what matters to you by changing charts, filters, layouts, and data sources.
You can build reports, analyse your data, and get insights whenever you need, without relying on IT or a data team.
You can download, share, and present your reports in various formats, such as Excel and PDF.
When you open your ad hoc report, let’s assume your finance dashboard, and you see that this month’s profit numbers are down, you probably ask, “Why?” Ad hoc analysis helps you answer that kind of question right away.
Ad hoc analysis is the process of digging into your data to find specific answers to one-time questions or to solve immediate problems that come up unexpectedly.
You’re not running a report. You’re examining your data on a deeper level to get more context on the numbers and facts shown in your report.
A great example of ad hoc analysis can be seen in the real estate dashboard we built for a property management company at Vidi Corp.
Each month, the team would use the dashboard to monitor performance. Over time, they identified some properties that were underperforming. Using ad hoc analysis, they were able to analyse the data to find out why.
How did they do it? They:
They did all this without coding and without requesting reports from IT. Just a few clicks on a user-friendly dashboard, and they had their answers.
Ad hoc analysis is usually done with the same tools you use for ad hoc reporting. The main difference is that reporting is about ‘what’ is happening, while analysis is about ‘why’.
Together, they help you stay proactive and make better decisions every day.
Microsoft’s Power BI is the most used self-service reporting tool. It features a drag-and-drop interface, robust data integrations, and real-time dashboards.
Microsoft has been a leader in the reporting software space since the launch of Excel. Power BI basically evolved from Excel and offers superior reporting automation and data visualisation capabilities.
Power BI is the ad-hoc reporting we use most as the data analytics agency for several reasons:
Since Power BI evolved from Excel, some of the Excel skills of your team would be transferable. especially Power Query and pivot tables. This gives your team a little head start for becoming self-sufficient in using a new ad-hoc reporting tool.
Tableau enables you to transform data into interactive visuals in seconds. It is ideal for in-depth analysis and is used by both analysts and business teams.
If we rank ad-hoc reporting tools by the quality of the software, Tableau would be a close second. It is a bit more expensive than Power BI, and you need to buy a license to develop reports. If you want to learn more about how Tableau compares to Power BI, you can refer to our guide on this topic.
Tableau is favoured by many developers for the following reasons:
Speaking from experience, some of our clients find Tableau a little bit too technical because of the abundance of functionality. Learning to use Tableau may seem overwhelming in the beginning, but once you get the hang of it, producing reports becomes very quick.
A user-friendly BI tool that’s part of the Zoho suite. Intelligent dashboards, built-in AI, and collaboration options.
Previously known as Google Data Studio, this free tool enables you to create real-time dashboards from Google Sheets, BigQuery, and other sources.
Looker Studio is mainly used for marketing analytics since it integrates well with data sources like Google Ads, Google Search Console, etc. There are also many cheap third-party Looker Studio connectors for sources like Facebook Ads, Klaviyo, etc.
Based on our experience, it is the best fit for external reporting, such as marketing agencies sharing dashboards with clients or businesses sharing reports with investors. The reason is that users of Looker Studio don’t need a license to view the report.
Looker Studio is best for simple reporting and data visualisations since it has many limitations for how you can customise the visuals and what formulas you can write. As a result, we often have to transform data using SQL to work around these limitations.
Looker Studio is fully web-based, which means that you can access it on a browser from any device. However, some companies don’t want their data to be stored online on Google servers. Unfortunately, Looker Studio provides no options for on-premise reporting, which might be a problem for businesses working with highly sensitive data.
DOMO connects to 2k+ data sources and focuses on real-time and team collaboration. It is quite SQL-heavy, so revise your SQL notes if you want to use this one!
Where DOMO excels is in offering the connection to 2000+ data sources out of the box. This is far more than any other tool offers. If your company has dozens of data sources to connect to, DOMO might be a good option for you.
The developer experience in DOMO is very SQL-heavy, so if you don’t write code in SQL, you might struggle with it.
DOMO is definitely the most expensive ad-hoc reporting tool that we have come across. They only target enterprise customers and offer custom pricing every time.
Now part of Google Cloud, Looker is more advanced and used by data teams to build scalable reports and data models for business users.
Looker is a different tool from Looker Studio. It is far more technical to use as all the data loading and transformation is performed in their facility called LookML. Based on our experience, Looker is also challenging to work with as it does not automatically aggregate the data in a pivot table format, the way that all the other tools do. As a result, all the breakdowns for every chart need to be coded.
Our experience with Looker is more limited, but I can say with confidence that none of our developers enjoyed it. You can also often see that many Looker Studio developers do not want to take on any projects in Looker because of how difficult they are.
Each of these tools supports on-demand, custom reporting. Your choice depends on your data, team skill level, and business needs. We’ll discuss choosing the right tool in more detail soon.
Ad hoc reporting provides your team with the speed and flexibility to gain data-driven insights when it matters most. Here’s how it helps your business:
Ad hoc reporting has many benefits, but there are issues you must avoid to reap all the benefits of ad hoc reporting:
If your data has errors or is incomplete, your reports will be misleading. Set up simple checks that clean your data automatically before it enters your reports. This saves time and builds trust in your numbers.
You may not want every team member to see all the data. Tools like Power BI enable you to control who sees what by setting rules that ensure each person only views the data relevant to them.
If your teams find the tool confusing, they won’t use it. Short, hands-on training sessions can make a big difference. Show real examples from their work so they see how helpful it is.
Starting with too many data sources can overwhelm new users. Begin with just one or two key ones, say your CRM or website analytics, so users can learn the basics before adding more.
If every team defines “success” differently, you’ll get mixed results. Set clear definitions for metrics, such as “revenue” or “conversion,” so everyone is working with the same understanding.
If your data is outdated, you could make the wrong decision. Ensure your dashboards refresh automatically so you’re always working with the most up-to-date information.
When choosing an ad-hoc reporting tool, ask yourself who you want to share the reports with. Many reporting tools (such as Power BI or Tableau) mainly support sharing reports internally within your organisation. This means that you will need to raise a paid license for everyone who needs access to your reports. While this is possible, it still causes extra hustle and might be difficult to coordinate. At the same time, tools like Looker Studio support external sharing of the reports to users without a license. You basically save yourself a lot of administration work by choosing Looker Studio instead of Power BI for external reporting.
Another important thing to look at is the data sources you want to integrate with, since those integrations take a long time to code. As a rule of thumb, Power BI integrates well with all the Microsoft sources, Looker Studio with all the Google sources and Amazon Quicksight with all the Amazon sources. Every tech company is essentially trying to include their ad-hoc reporting tools into its ecosystem.
Finally, every ad-hoc reporting tool has certain limitations for visualising data, such as a lack of certain charts or ways to customise them. Working around those limitations is usually possible but requires a lot of thinking, creativity and technical skills. If you need to produce advanced data visualisation, tools like Power BI or Tableau would be the best fit. However, for simpler analysis, you can choose Looker Studio and make the most out of its unique advantages.
The tool you choose should suit your needs and be easy for your team to use. These are some pointers to make the right decision:
Be sure that the tool you choose connects easily to the systems you already have set up, whether that be ERP, CRM, or Google Analytics. If it does not, your team may face serious challenges working with the necessary data.
The tool should be easy enough for people with no tech background to learn in a short time. If the interface is complicated, it will never be used, no matter how powerful the tool may be.
Pick a tool that can handle large data to ensure it never slows down or crashes as your business and data expand. Your selected tools are meant to grow with you, not hold you back.
If you’re handling customer or health data, you must ensure your tool supports all the compliances like GDPR or HIPAA to be compliant yourself and protect user privacy.
In fact, do not just limit yourself to investigating only a monthly subscription fee. Calculate training costs for your team, costs related to storing huge datasets, and fees for advanced-level features. Add it all up so there are no surprises later.
Simply put, the best tool should fit your data, your people, and your goals at the same time.
The fastest way to adopt a new reporting tool is by working with business intelligence consultants. The consultants would typically do the most technically challenging bits of development and then pass the reports to the client. Your team could then learn the new ad-hoc tools by customising created data visualisations and adding new analysis to the created reports.
A longer way to adopt new reporting tools is by having your team develop the reports from scratch. Your first reports would likely not follow the best practices, but your team would gradually learn new, important skills. Speaking from personal experience, it took me 1.5 years to start developing Power BI reports that truly follow good reporting practices.
If you want to develop your reports in-house, it is important to choose a reporting tool that has a large community of users and good learning materials, such as Power BI or Tableau. This way, your team would find answers to their questions much quicker and make more progress in the same amount of time.
Follow these steps for a smooth implementation of ad-hoc reporting in your company:
Phase 1: Start with one department
Start with, for example, the sales team first as a test case for the tool. That way, you can concentrate your effort there and address any problems before the entire company is affected. Also, sales departments usually have clear-cut goals and abundant data, which makes them a great place to start.
Phase 2: Clean your data and define KPIs
Before any report building begins, clean the data to eliminate all possible inconsistencies and ensure that there is no missing data. Second, have an agreement with your team on which key metrics matter, i.e. the conversion rate. Clean data and clear KPIs make reporting easy.
Phase 3: Build a few template reports
Develop 3-5 simple templates that your team can immediately start utilising, such as a sales pipeline report, a campaign tracker, or a weekly performance summary. These reports will deliver quick results to them and help them get started more confidently.
Phase 4: Train users with real examples
Conduct training sessions that allow users to explore the tool with data from their own work experience. Show the users how to apply filters and drill down charts in order to answer questions confronted daily. This brings direct relevance to training.
Phase 5: Monitor usage and improve
After the launch, measure the tool’s usage. Find out where people get stuck. Collect feedback, address issues that block usage, and continually refresh your templates and training. The more support you offer, the greater the value your team will derive from it.
Ad hoc reporting is getting smarter and more useful. These are some trends that show where it’s heading and what to expect next:
Modern tools utilise AI to identify anomalies in your data and provide explanations immediately. For instance, if sales for any product drop by 20%, the tool can determine both the drop and its cause without requiring anyone to conduct the analysis. AI technology, such as Zebra.ai, used in tools like Power BI, allows you to gain insights from your data by asking questions in plain English. There’s a new set of possibilities when AI meets reporting.
Increasingly, day-to-day applications are being finely embedded with analytics; CRM tools like Salesforce are a good example. This approach leads to an enhanced user experience and increased efficiency in decision-making.
According to Grow.com, more than 70% of professionals check their business data on mobile devices several times a day; hence, tools are now designed to provide real-time alerts and interactive dashboards.
Ad hoc reporting tools give you the freedom to explore your data, find quick answers, and make smarter decisions without waiting on anyone else. When done right, they save time, cut costs, and empower every team.
If you’re ready to realise the full value of your data, reach out to Vidi Corp Data Analytics Consultancy. We’ll help you choose the right tool, set it up, and get your team using it with confidence.
Standard reporting is the one that is fixed and scheduled. Ad hoc reporting, appropriately named, enables you to generate custom reports on demand to answer questions as they arise.
Ad hoc analysis is a one-time, in-depth investigative analysis of your data to solve a particular problem your business is facing or to understand why something happened.
Not entirely. Ad hoc reporting interjects speed and flexibility into the mix, but traditional BI is still required for routine tracking, assessing long-term trends, and the more complicated aspects of data modelling.
