When it comes to introducing new technology features in Excel, particularly those designed to bring powerful analytics to the masses, there are two possible approaches. These approaches can reveal much about the difference between honest communication and social media-driven hype, which often misleads audiences into thinking these capabilities are groundbreaking when, in reality, they’ve existed for decades.
One approach is straightforward: introduce a powerful, industry-level concept or tool, explain what makes it remarkable, and then highlight how it has been adapted into Excel for practical everyday use. This approach is balanced, giving users context about the original technology’s capabilities, limitations, and real-world applications, along with the reasons for its adaptation. For example, technologies like SQL Server Analysis Services (SSAS) and its OLAP capabilities are well-known within enterprise settings, enabling massive data processing and analysis beyond the constraints of local machines. Integrating a lighter version of this technology into Excel through features like Power Pivot allows Excel users to work with larger data sets and gain access to a powerful analytics engine.
Alternatively, there’s the hype-driven approach, which pitches these features as spectacular, unprecedented innovations. In this narrative, Excel becomes a hero by suddenly offering “industrial strength” data analysis without any mention of the original tools or established capabilities. This approach fuels social media channels, leveraging influencers to promote these features as if Excel has magically transformed overnight.
Power Pivot: Industry Power in Everyday Hands.
Power Pivot introduces an in-memory engine, known as “xVelocity” or VertiPaq, that allows Excel to handle larger volumes of data than was possible with traditional Pivot Tables. Before Power Pivot, Pivot Tables in Excel were limited by data set sizes and local machine processing power. With Power Pivot, Excel now leverages a compressed data model, allowing more data to be analyzed without massive performance hits. Yet, this capability has been quietly embedded in Excel for years through database connections and Microsoft’s own external query options.
The punchline? Relational data, often pitched as the “new” capability of Power Pivot, is actually not new at all. As far back as 20 years ago, Excel users could link external data from Access databases into Pivot Tables. These databases could handle multiple tables with relationships, creating data models and querying from relational sources directly in Excel. Microsoft Office certified this ability in its exams, and advanced Excel users were tested on it.
We knew this ages ago. Twenty years ago, Simon Hurst–a recognized leader in Excel education with the Institute of Chartered Accountants in England and Wales–demonstrated the concept of linking tables in Access as the data source for Pivot Tables, proving this feature’s longevity. The feature in Excel in those days was MS Query. His audience was impressed by the ability to overcome Excel’s then 65,000-row limit by drawing data from Access, which could handle hundreds of thousands of records. At the time, our data processing limits were dictated by memory and hardware, yet even back then, advanced Excel users could import 250,000 rows of data, as on one of my solutions at Edexcel.
Not only that, Simon showed how two tables are joined in Access to create what we today call a ‘data model’. This was through Excel and Get External Data which was in the Data tab of the menu.
Did I say this was 20 years ago?
But as new features emerge, the emphasis on context has faded. Today, social media influencers may frame Power Pivot’s relational data model as groundbreaking, obscuring its long history. Many influencers either ignore or are unaware of these capabilities’ origins, which contributes to the illusion that Excel’s data modelling capabilities are fresh innovations.
The Problem with the Hype Machine.
This omission of context isn’t just misleading; it paints a distorted picture of what is “new” in Excel. Social media thrives on “spectacular” announcements, yet often omits the full history or foundational uses of these tools. Many influencers have no knowledge of SQL Server Analysis Services, OLAP, or similar tools; this makes it tempting to simply present each “new” feature as a dazzling, standalone revelation.
Take Power Query, for instance. While Power Query offers excellent ETL (extract, transform, load) capabilities and automates data transformations within Excel, it’s often oversold. Influencers will present Power Query’s functionality without acknowledging that ETL concepts have existed for decades and that similar solutions have been used in databases and reporting systems long before Excel incorporated them.
In many ways, Excel’s evolution is more about adapting and scaling down enterprise technology than inventing from scratch. Features like Power Pivot and Power Query do give Excel users tools that would otherwise be inaccessible, but the basics of these technologies have been around for decades.
Concluding Thoughts: Balancing Excitement and Reality.
For those of us interested in Excel’s potential for real-world, enterprise-level applications, it’s crucial to embrace new features with the right perspective. A balanced approach in education would explain the historical context of these features, the technology they borrow from, and why this matters for the business user. While hype sells, a more transparent narrative could better prepare users for the actual power–and limitations–of these tools.
When new features are announced, they should be framed within the context of what’s already achievable. Excel’s role as a vehicle for enterprise-level tools should start from a place of honesty and accuracy, even if this approach doesn’t create the same buzz as social media’s “fireworks and confetti” method.
The next time you hear of a “groundbreaking” Excel feature, consider its roots and what the feature actually offers.
This is a podcast by HIran de Silva. Narrated by Bill.
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