6 Key Differences Between Data Analysis and Reporting

Once you have data on hand, your job is far from done. You’ll need to collect it all together and put it into context to get real value from it.

These tasks, data analysis and reporting have equally crucial roles to play in business. When we consulted 45 professionals about data analysis and reporting, more than half of them told us that exploring data and reports and organizing them into informational summaries are equally important.

But, what makes data analysis and reporting different? We have the above basic definitions from our survey, but so much more work goes into each process.

We asked survey respondents whether they would choose data reporting or analysis to understand the differences between the two steps more effectively. In this blog post, you’ll learn more about these two subjects:

• What Are Data Analysis and Reporting?
• 6 Differences Between Data Analysis and Reporting

Let’s dig in.

What Are Data Analysis and Reporting?

Before you dive into the differences between data analysis and reporting, let’s start with some working definitions. 

PhotoAiD’s Natalia Brzezińska thinks of these processes as two sides of the same coin, using an analogy from everyday life. “I think it is similar to checking your bank account at the end of the month,” Brzezińska begins.

Here’s how Brzezińska explains data reporting: “We all ask ourselves: where has my money gone? It’s a field of data reporting. Gathering data (money spent) shows your performance (empty bank account). This information leads to questions (where has my money gone?). Data reporting tools aim to gather and present data in charts and tables to determine whether a change has occurred. In response to a noticed change, questions arise.”

What about data analysis? “Data analysis, on the other hand, is the interpretation of information in the context. To find an answer to your question (where has my money gone?), you explore data and try to extract meaningful information (how much have I spent on food/ clothes/ environment?). Then, you can look for a solution (what savings can I make?),” Brzezińska says.

So, as you go into the differences our respondents listed, you can start with these definitions:

• Data reporting: Gathering data into one place and presenting it in visual representations
• Data analysis: Interpreting your data and giving it context

6 Differences Between Data Analysis and Reporting

Respondents mentioned these six main differences between data analysis and reporting:

1. Required Skills
2. Order of Operations
3. Time Needed to Implement
4. Ease of Automation
5. Impact on Strategy
6. Data Context

1. Required Skills

Many of the professionals we consulted consider data analysis a higher-skill task than data reporting. This isn’t to say that reporting doesn’t matter as much because of the difference in skill level, of course — you’ll learn more about its importance throughout this blog post. But, data analysis takes more advanced knowledge and practice to master compared to reporting.

In fact, when we asked respondents about the number of data analysts on their team, over half of them said they have more than one. That’s a significant number, considering how many of our survey participants come from SMBs.

According to Red9’s Mark Varnas, “Data analysis is a more difficult task than data reporting because it requires knowledge about different analytical models and statistical techniques. It also requires the ability to draw inferences from raw data and high-level understanding of the business problem.” Simply put, you need advanced analytical skills to succeed.

“It is in data analysis that the story is formed – and translated – to the average person,” says Carly Cais of ElleSpark. “…Data analysis is critical for early-stage companies, especially those that are pitching investors and VC’s – because those groups always need a compelling ‘story’ to win them over. Investors invest in the story (and the implied potential), not in plain reports. That is why data analysis and advising on future business decisions is part of our core offering to companies: it’s not in what you show but instead in how you describe it.”

For PeopleFinderFree’s Eden Cheng, the skills associated with data analysis can serve you well outside of analytics: “Data analysis broadens your capability to solve various problems. By choosing this, you can gradually develop problem-solving skills.”

Cheng continues, “Your competency to contemplate analytically and approach challenges in a correct way is a top-notch and useful skill. Therefore, it will be immensely valuable not only in the professional world but also in daily life too! The value of deductive reasoning proficiencies is enormous, which explains that being capable of looking at numerous pieces of data and conclusion is a must-have skill for any employee.”

Related: 8 Common Mistakes in Data Analysis for Marketers to Avoid

However, none of this is to say that data reporting and analytics involve zero skill. Bond Media’s Anthony Mixides prefers data reporting over analysis and frames each task through different skill sets. “While reporting can connect cross-channel data, give comparisons, and make information easier to grasp (think of a dashboard, charts, and graphs, which are reports, not analysis reports), analysis understands the data and makes action suggestions,” Mixides explains. 

2. Order of Operations

Since data reporting organizes and visualizes data, it must happen before you can perform data analysis. Even if you decide to complete only your data analysis in-house, you’ll need to have some form of data to work with, such as an external report.

“Data analysis and data reporting form part of a single chain of events, only that one comes considerably before the other,” Sally Stevens of FastPeopleSearch tells us. “Data reporting looks at the raw data and translates it into information.”

Stevens explains how analysis follows reporting. “Reports don’t give conclusions, but a proper analysis of the question raised in the reports will. Data analysis provides answers to the why, and also gives the way forward.”

When we asked Financer’s Johannes Larsson to choose between analysis and reporting, Larsson couldn’t. “I won’t choose one because they are useless without the other. Data reporting is the process of turning raw data into understandable information. Then, business analysts analyze this information to turn it into invaluable insights using data analysis,” Larsson elaborates.

Larsson concludes, “People need data reporting for data analysis to occur. However, data reporting results are useless if they can’t use the information generated into understandable insights.”

Jordan Brannon of Coalition Technologies has similar thoughts on the subject. “Data analysis cannot exist without data reporting. It’s important for us as a marketing agency to extract information and represent it in a readable format, and it’s equally important to explore and analyze the information collected,” Brannon says.

In sum, data reporting builds the foundation you need to perform excellent data analysis. You must have a data report available to analyze that data in the first place.

3. Time Needed to Implement

After you get a finished data report or analysis, someone will need to implement that information. Depending on your business structure, it can take longer to implement one than the other.

As a manager at Octiv Digital, Jeff Romero prefers data reports because of their ease of use. “…as a manager of my company, I need to be able to quickly glance at reports from a 30,000 foot view for clients and I don’t have time to dive in too deep. Meanwhile, data analysis is ongoing for all clients,” Romero tells us.

InVideo’s Sanket Shah also chooses reporting over analysis for its fast implementation. “Being a SAAS business, if given a choice between data analysis and data reporting, our organization would pick data reporting. Data reporting, in my opinion, is an all-encompassing procedure. If the right effort is put to report and record data, it automatically provides you with an insight into the state of matters in a business” 

Yet, at the same time, Patti Naiser from Senior Home Transitions prefers analysis for similar reasons. “Personally, I favor data analysis as the meaning of all that information is right in front of you! As a business owner, I may not always have time to conduct a deep dive into the data to extract meaning. It is therefore beneficial when the data is in front of me as it makes the decision-making process all the more easier and less time consuming!” Naiser says.

So, when you consider the time you’ll need to take performing and implementing data analysis and reporting, keep your industry, work style and team structure in mind. Will the people using your work need a broad overview or deep-dive available? If your team members wear many hats, will the same person report, analyze and use the data?

4. Ease of Automation

Since data analysis requires a human touch, it’s harder to automate than data reporting. On the other hand, analysis’s need for human involvement lends it its strengths.

Confection’s Quimby Melton compares data reporting and data analysis to plot reading and close reading skills: “As an English major, I can’t help but think of the difference between data reporting and data analysis as similar to “plot reading” and critical (or “close”) reading. There’s certainly a place for entertainment, but the first involves a passive relationship with the text. It enters your mind for a moment, and then it’s gone. Close reading, on the other hand, involves holding information in your mind, building some sort of interpretive framework around it, and outputting something new, interesting, and valuable, something other people can use to better understand the text, themselves, and/or the world around them.”

How do these concepts apply to data? “Close reading” data works the same way. It transforms cold information into warm insight and actionable intelligence. In the long run, AI may challenge me on this. But I think this faculty is uniquely human. It’s our greatest gift, and anyone who can do it well is a valuable asset indeed,” Melton remarks.

Because of data analysis’s impact on business decisions, content marketing agency founder Alex Birkett recommends automating as much of your reporting as possible. “Reporting should, by and large, be automated and passive (and could lead to data analysis questions if there are aberrations from your projections),” Birkett elaborates.

But, this isn’t to say that you shouldn’t have someone on your team dedicated to data reporting. Over three-quarters of our respondents have a reporting analyst on-staff:

Plus, despite automation’s growth over time, most of those participants hired their reporting analysts in the past three years or earlier.

Look for a balance between reporting automation and human oversight that works for your organization. Sometimes, you can assign reporting to someone with multiple roles, but if you can afford automation technology, consider investing in it.

5. Impact on Strategy

Most businesses collect data to inform some kind of strategy, whether for customer retention, finances, lead generation, or another aspect of the business. Most of the survey respondents who contributed their opinions agree that analysis has a much bigger role to play in building strategies than reporting.

“If I had to choose between data analysis and data reporting, I would choose data analysis, because reporting data, without analyzing it, doesn’t serve much purpose,” says HMG Creative’s Matt Benevento. “A data report that is automatically generated and has no context only scratches the surface of a campaign; it will not help to inform your strategy and will have less impact in building client trust. Data analysis is crucial for understanding the impact of your efforts and planning your ongoing strategy.”

Here’s how Structured Agency’s Nick Shackelford puts it: “Reporting incorporates data to convey the performance of your business. However, an analysis uses the data to find solutions to questions and pain points. Although it may seem like semantics, one simply shows you where you stand during a given period. The other effectively enables you to employ a strategy and assess where and how to use capital and methods to increase profit and cut losses.”

As someone who prioritizes strategy, Linda Chavez from Senior Life Insurance Finder agrees. “While data reporting makes information easier to understand, analysis interprets the information to provide actionable insights so managers can form strategies based on them. Analyzing data about the operations of a business can help improve operational efficiency, while marketers can also use it to better understand their customers. My preference for data analysis over reporting comes from the fact that reporting is only useful in communicating information in an easier way. Analysis, on the other hand, can be used to make informed strategic decisions.”

Data reports give you a look into your organization’s current performance. Meanwhile, analysis turns that data into actionable insights to guide your future actions.

6. Data Context

While reporting provides data without context so you can draw your own conclusions, analysis makes those conclusions for you to deliver context.

Will Henry of Bike Smarts chooses data analysis over reporting but recommends using both to see your data with and without a narrative. “I would opt for data analysis because it is more important to know what the conclusions are rather than just knowing how they were reached. Data analysis looks at raw data and distills it down to information that will yield insights you can use to make better decisions. Data reporting, on the other hand, summarizes raw data into a story that conveys its findings in an easy-to-digest format,” Henry says.

Henry concludes, “The choice essentially boils down to whether you want just the facts or also find it useful that those facts are told in a sequence with context behind them. Data reporting makes trends easier to spot over time but analysis lets you drill deeper for meaning within certain ranges. We’d advise using both so your interpretations draw on as much factual base as possible.”

YB Digital’s Yoann Bierling considers data analysis a necessity because of the context it provides. “Data analysis is a broad look at big data available, which is the only way to find interesting new insights into what’s really happening in business. On the contrary, data reporting focuses on data excerpts already identified, and while it supports follow up on pre-defined KPIs, only looking at reports might make us miss important peculiarities hidden in data,” Bierling explains.