Introduction
 In the early days of personal computing, accounting software was often clunky, inaccessible, and reserved for professionals with deep financial expertise. Then came QuickBooks, a game-changer that democratized financial management for small businesses. Launched in 1992 by Intuit, QuickBooks offered intuitive reporting features that allowed entrepreneurs to track expenses, generate invoices, and produce insightful financial statements with unprecedented ease. 0 What started as a tool for simplifying bookkeeping evolved into a massive ecosystem, with Intuit leveraging user data to fuel growth and innovation. Today, as artificial intelligence (AI) reshapes industries, businesses must weigh the convenience of platforms like QuickBooks against the risks of ceding control over their data—their intellectual property (IP)—to tech giants. This article explores QuickBooks’ history, Intuit’s data-driven ascent, and why firms should prioritize owning their financial data in an AI-dominated future.

The Revolutionary Beginnings of QuickBooks
Intuit was founded in 1983 by Scott Cook and Tom Proulx, inspired by the frustrations of manual financial tasks like balancing a family checkbook. Building on the success of their personal finance software Quicken, Intuit introduced QuickBooks in 1992 as a DOS-based program tailored for small businesses. Unlike the rigid, standards-heavy accounting systems of the era, QuickBooks prioritized user-friendliness. Its reporting capabilities were a standout feature: users could effortlessly generate profit and loss statements, balance sheets, and cash flow reports, providing real-time insights that empowered owners to make informed decisions without hiring accountants.
This accessibility drove rapid adoption. By 2000, Intuit had released Basic and Pro versions, followed by industry-specific editions in 2003.  The software’s appeal lay in its ability to handle core tasks like invoicing, payroll, and inventory tracking while offering customizable reports that highlighted trends and performance metrics. For many small businesses, QuickBooks wasn’t just software—it was a lifeline that transformed chaotic ledgers into actionable intelligence. As adoption surged, QuickBooks Online launched in 2001, shifting toward cloud-based services and marking the beginning of Intuit’s data-centric evolution

Intuit’s Data Capture: Building a Financial Empire
As millions of businesses migrated to QuickBooks, Intuit amassed an enormous trove of financial data—from transaction histories and payroll details to customer interactions. This wasn’t accidental; it was strategic. By the mid-2010s, Intuit had pivoted from a software vendor to a data-driven platform, using aggregated user data to enhance products, personalize experiences, and create new revenue streams. 
Intuit’s monetization practices exemplify this shift. The company leverages data for ecosystem growth, including AI-powered insights, targeted marketing via Mailchimp, and integrated services like payments and payroll.  For instance, in its Enterprise Suite, Intuit uses customer data to automate marketing campaigns and uncover revenue opportunities.  This “data moat” has propelled Intuit’s valuation to over $170 billion, with online ecosystem revenue growing 20% in recent years.  Acquisitions like Credit Karma (for $7 billion) and Mint further expanded its data assets, enabling cross-product synergies where user information fuels personalized financial advice and upsell opportunities. 
Critics argue this creates a “kingdom” where Intuit controls vast swaths of business financial data, using it to refine algorithms and maintain market dominance. While Intuit emphasizes privacy and responsible data use—rooted in principles like transparency and fairness—the reality is that users often unknowingly contribute to a system that benefits the platform more than individual firms. This data aggregation has allowed Intuit to scale efficiently, but it raises questions about who truly owns the insights derived from a business’s operations.

The AI Era: Amplifying Opportunities and Risks
Intuit’s embrace of AI marks the next chapter in this story. Since declaring its AI-driven expert platform strategy in 2019, the company has integrated generative AI across products like QuickBooks, TurboTax, and Mailchimp.  Initiatives like Intuit Intelligence—a system that unifies data to provide AI agents for tasks such as forecasting, payroll automation, and actionable insights—process financial data up to 10 times faster than traditional methods. Tools like Intuit Assist automate accounting workflows, combining AI with human experts to deliver personalized experiences. 
This AI prowess is powered by Intuit’s proprietary datasets, drawn from over 100 million users and trillions in transactions. The company uses machine learning to predict cash flows, generate reports, and even democratize access to financial expertise through platforms like Prosperity Hubs. However, this reliance on centralized data introduces risks: biases in AI models, potential data breaches, and ethical concerns around transparency. Moreover, as AI evolves, firms risk becoming overly dependent on Intuit’s “black box” systems, where algorithms trained on collective data may not fully align with individual business needs.

Taking Ownership: Why Firms Must Reclaim Their Intellectual Property
In this AI landscape, data is the new IP— the raw material for innovation, competitive advantage, and growth. Yet, by entrusting platforms like QuickBooks with their financial data, businesses inadvertently hand over control. Intuit’s terms allow it to use anonymized data for product improvement and AI training, potentially turning a firm’s unique operational insights into generalized tools that benefit competitors. 
Firms should consider alternatives to avoid this trap. Self-hosted accounting solutions, open-source tools, or competitors like Xero and Sage offer greater data sovereignty, allowing businesses to retain full ownership and integrate custom AI without third-party dependencies. For AI adoption, companies can invest in in-house tools using frameworks like open AI models, ensuring their data fuels proprietary insights rather than a vendor’s ecosystem.
The implications extend to compliance and security: owning data reduces exposure to platform-wide vulnerabilities and aligns with regulations like GDPR, which emphasize data minimization and user control. Ultimately, while Intuit’s “heavy lifting” provides convenience, true empowerment comes from treating financial data as a strategic asset—guarding it, analyzing it independently, and leveraging AI on your terms.

​Conclusion
QuickBooks’ journey from a reporting powerhouse to an AI-enabled giant illustrates the double-edged sword of tech platforms: immense value paired with subtle power imbalances. As AI accelerates, businesses must decide whether to build within someone else’s kingdom or forge their own. By prioritizing data ownership, firms can harness AI’s potential without sacrificing their intellectual property, ensuring sustainable prosperity in an increasingly data-driven world.

This presentation focuses on helping accountants understand that financial information is absorbed in different ways by different people and offers telling a financial story as solution to bridge the gap between tabular reports and the illusive dashboard

Having a long career in financial reporting, I started using Power BI tools before the very first version was called Power BI. While I wrote this article in 2022, it remains as relevant today as it did when I wrote it. It's original publication was on The Woodard Report

​Many years ago I worked with the accounting department of a semiconductor manufacturing equipment company. The board wanted the accounting team to give them a tool to get better information on how they could see the impact of different choices they were facing with regard to inventory levels.

As an example, if they invested in more inventory how would that impact the balance sheet and income statement? If they aimed at inventory turns of 1% more or less, how would that change financials? Back in 2000, getting information like that to display meant that I had to employ my programming skills to pull data out of the accounting system and feed it to a graphics package.

That was the start of my interest in analytics and reporting, an interest that grew until I built a business specifically around transforming QuickBooks data into actionable information. And I invest my energy into our industry by providing training to other accountants and bookkeepers just like you. For example, this year I'll be teaching "Introduction to Power BI" at this year's Scaling New Heights conference in June in Orlando. For more information on my session and the other more than 100 sessions that will be offered, you can view the training schedule here. 

What Is Power BI?
Power BI is an enterprise business intelligence platform, This scalable platform allows you to connect to all of your data sources with the scale to analyze, share, and promote insights across your business while retaining data accuracy, consistency, and security.

What Does Power BI Do? 
Today, the same kind of information that used to require serious programming skills can be generated with ZERO programming knowledge by using Power BI. Of course, it’s important to know that Microsoft didn’t create Power BI overnight but has been at this for decades, and it shows!

Simply put (and as Microsoft describes it), Power BI bridges the gap between data and decision-making. 

In the enterprise software world, an organization known as Gartner has made a business out of taking a deep dive into various solutions areas and providing a detailed analysis at a cost. Their analysis is widely recognized as being the "gold standard" for understanding what the best solutions are for a given market. In Gartner's analysis of Analytics and Business Intelligence Platforms, Power BI has been the leader for many years.

This is Power Query article was also commissioned by Transaction Pro with I was an expert blogger

The below article originally appeared on the Transaction Pro as an example of how Power Query could be used in conjunction with their tool to produce a unique report

I​t’s 5:00 am and I can’t get this out of my head until I write it down so here I am. If you pop “accounting” in the google engine today’s top result is from Investopedia where they say:

Accounting is the process of recording financial transactions pertaining to a business.

From the beginning in business, owners have needed to understand if their toils were bearing fruit. At the earliest, an abacus was used along with the accountant’s intellect with an aim toward that goal. As time has progressed, so has the quality of tools that accountants have at their disposal to not just collect, but also to categorize, aggregate and analyze. It’s because of this view that, although I am deeply technical, I consider myself an accountant.

Even though I started my accounting career over 40 years ago, thankfully I didn’t have to start my accounting career using an abacus. “Back in the day” my Silicon Valley-based high school had classes where I learned how to use a 10-key adding machine and a typewriter. In my senior year, I even took a technical class labeled “computer-assisted accounting” where I learned the mysteries of punched tape machines and calculated auto part inventory totals with punched cards. A bit later when I finished my accounting degree and was working in the Joint Venture (JV) accounting department of Chevron, I started putting those learnings to work.

In an odd way, a project I did in the JV accounting department 30+ years ago is just as relevant today as it was over 40 years ago. As an A/R clerk, I was tasked with the unenviable job of helping to collect their accounts receivable by providing the documentation necessary after their ambitions for new deals exceeded their systematic capacity to properly deliver it. Then, just as it is now, over time business ownership changed hands. Their case was a much more extreme one because many of their partners were small. Because of that, anytime a partner living their life married, divorced, died or for some other reason divided their interest, new invoices needed to be generated to reflect the proper ownership.

A recent project I completed where we were exporting reports from QBO and calculating ownership earnings showed that even today we struggle with many of the same issues

In my old project, I suppose I could have just sat down and keyed those entries in until someone told me to do different but after studying accounting theory for 4 years, I suppose I didn’t want to settle for a job keypunching numbers. In my mind I did what any good accountant would do - I found a way to improve the process of reporting the financial transactions so it could be done faster and more predictably. Rather than typing out every charge in a spreadsheet and calculating the amount due based on the new ownership interest, I found a way to get a machine to spit out an invoice with the right amount.

In much the same way, today’s transaction feeds from our financial institutions are repurposed using rules so that rather than typing in and classifying every transaction we can simply help write the rules for how that transaction should be classified. Many may not consider it so, but I would dare to say that bank rules are artificial intelligence and learning to leverage them is every bit as much accounting as my early days of learning a paper tape machine.

​Originally, QuickBooks Desktop effectively operated more like an Excel workbook, storing data in flat information files. QuickBooks later changed to use an actual database. Fortunately (and unfortunately) a database engine is a very complex thing and while Intuit has provided a lot of tools to help manage the complexity, too often those tools and best practices are not used. My goal in this article is to help you understand why maintenance tools are needed to make sure your QuickBooks database stays safe.

The information in this article is a preview of one of my sessions at Scaling New Heights, 2021. I hope to see you there in my breakout sessions "QuickBooks Desktop Reporting: A Deep Dive into Using the Data You Work so Hard to Put into QuickBooks" and "Making a Great Dashboard with Power BI."

To maximize your use of QuickBooks, there are several core ideas you need to understand.

The QuickBooks database is a complex structure.

When you look at a visual representation of the QuickBooks Desktop’s database (and you are not meant to be able to read the words in this image), you will see the scope of the database.

As accounting professionals, we don’t enter data just because we want that data. Instead, we put data into the QuickBooks database to be able to get aggregated information out of QuickBooks. Although that low-level data on its own is useful, the higher-level information we extract is more important. For example, when you enter a sales invoice, what you may want is the information around historical sales for compliance (tax) or maybe to spot trends to project future sales.

Because none of us would put up with long wait times to save, retrieve or maintain long strings of redundant data inherent in financials transactions, QuickBooks was designed primarily as what is called an Online Transactional Processing (OLTP) database. These databases are characterized by a complex interrelationship of separately stored information that, in many cases, are linked by codes that identify a unique record like an account, an item or a customer. The ability to store just a small code instead of a long customer name not only saves space and reduces the speed at which an invoice can be saved, it also reduces the number of records that need to be updated when a name changes.

Let’s take a transaction level look at what happens in the database. When you create an invoice, for example, you are actually entering data into ten different tables within the database - summary information, customer information, details, inventory line, serial/lots, linked transactions, audit trail, preferences, entity notes, and billing rates. When you consider that each inventory item may impact multiple inventory lines with multiple series and lots and that you create audit trail changes, you begin to appreciate how complex the data structure can become complex.

Stuff happens.

As you can see, the QuickBooks Desktop database is a very complex series of tables and while Intuit engineers work incredibly hard to ensure that no data is ever lost and while they do all they can to prevent mistakes, ALL applications and database as complex as QuickBooks will have "stuff" happen.

People sometime refer to a “corrupted QB file” but I’m not sure that’s a great way of understanding what is really happening. The Sybase database engine which is at the heart of QuickBooks after all is world class and can store way more information than our QuickBooks files hold, so what’s the real issue?

Simply put, what most people see as corruption stems from is an unexpected situation that comes about while updating QuickBooks.

As a database professional that sees hundreds of files every year, we certainly see some patterns erupt in corruption. Because updating a file is realistically the only way a file becomes “corrupted”, all of these factors below are all just different ways the risk is increased.

• Operating platform – The variety of ways QuickBooks desktop can be run, from really old windows 7 machines on a wifi network to the latest hosted environments is a core strength as well as a risk simply because of all the variables introduced. Issues come from things outside of Intuit’s control like inefficiencies in data storage (fragments) to underlying windows issues. Human error also comes in to play, for example when one machine is updated but not another or permissions are changed in a way that causes issues. Finally, most of use have seen at least once the power cut to a computer running QuickBooks
• File volatility - The more activity a file has (sometimes measured in file size, the depth of the transaction, the number of customers, etc.), the greater the opportunity for problems to occur
• Age of file - Years of use can also impact your risk since, over those years, many changes in how data is handled in the program have happened. Given the depth and breadth of QuickBooks, updates to ALL historical data can be hard for engineers to map out. For example, it took Intuit 3 years to port the information from their old methodology to the current SQL Anywhere platform, effective 2006.
• How you use QuickBooks - As new capabilities come and go, it’s always possible for something to be over looked.

All backups are not the same.

Many companies tell me that the tech guy handles their QuickBooks backup. That would be great EXCEPT for the fact that most tech guys are going to use their tools to save a copy of the QuickBooks files and call it a day. That may work (I know it may have worked for you for 20 years), but it is not bulletproof.   The reason this kind of backup is not very reliable is related to the fact that, as detailed earlier, QuickBooks is a complicated database file.

What should we do then?

I mentioned maintenance tools at the beginning of this article. The number one underutilized tool in my opinion is the QuickBooks automated backup. Setting up the backup with verification AND monitoring it will not just give you a fallback position, it can alert you to issues in your data before they’re insurmountable.

Here’s how: Back up your QuickBooks Desktop company file (intuit.com).

Since QuickBooks is deployed in a lot of environments, a caveat here; you should always do your own testing and validation before relying on a backup plan. Hosted environments, Qbox and other add-in products can all affect this Intuit tool.

Finally, the biggest reason to do the Intuit backup instead of  a file backup is that before this backup runs, Intuit made sure to include a maintenance program that verifies the database BEFORE doing a backup. This verification is critical to the long-term health of your database.

A little tidbit that might intrigue you here; as a part of the maintenance, you may save some disk space and improve the speed of QuickBooks

This slide deck was originally presented in the height of the COVID pandemic.  The reality was that MANY companies came to find that critical reports that had been relied on for a long time has ZERO documentation and could only be created by the author. Enter a presentation on how to use Power Query to create reports with documented, repeatable steps.

Far more than a blog entry, this is a copy of the slide deck I used in 2020 to introduce Power BI Dashboards to the attendees at Scaling New Heights 2020