Whether examining reports of sales revenue, production output or administrative expenses, it’s often valuable to examine the underlying data in more detail. That’s what data drilling is all about. It’s a simple analysis technique that businesses can use to explore data and gain insights into the causes of trends. For example, if a national sales report shows unusually rapid revenue growth, a sales leader can drill down into the report to find out which regions or products contributed to the increase. Ultimately, data drilling helps companies make more informed business decisions to increase revenue and improve operational efficiency.

What Is Data Drilling?

Data drilling is a business intelligence (BI) technique that helps companies analyze information by providing different views of the data in reports, charts and spreadsheets. It’s a simple and valuable tactic that can help reveal the cause of trends. Most commonly, data drilling is used to examine the detailed information that lies behind the summary data shown in reports. Often, businesses can drill down to see progressively more detailed views of information that let them pinpoint the precise factors driving trends or anomalies.

Key Takeaways

  • Data drilling is a simple, fundamental analysis technique that helps to reveal the causes of trends.
  • It can be applied to analyze data in reports, charts and spreadsheets.
  • Drill downs are the most common type of data drilling. Drilling down provides more detailed views of the data behind the summary information in reports.
  • Drill hierarchies determine the pathways companies can use for data drilling.

Data Drilling Explained

The ability to summarize vast amounts of raw data in reports and dashboards is critical for monitoring and improving business performance. But just as critical is the ability to explore the data to gain a better understanding of the trends and factors driving them. Data drilling helps companies do that.

There are several types of data drilling, including drilling down, drilling up and drilling across (also known as drilling through). Drill-down analysis is the most common. As the name suggests, it involves delving into summary information for a more detailed view of the underlying data. For example, a sales leader could drill down into a national sales report for a more detailed view of sales in individual regions and cities, then drill down within each city to examine store-by-store revenues. Companies can also drill up from specific details to more general information for a big-picture view or drill across to other related datasets.

Data-drilling capabilities depend on how the underlying data was originally collected and categorized and how it’s stored — which is often done in a data warehouse. The more fine-grained the original data, the further you’ll be able to drill down to view detailed information.

What’s the Difference Between Drill Downs and Drill-Through Reports?

Drill downs and drill-through reports both provide ways to obtain more information about items in a report. An important aspect of business intelligence, drilling down into data helps you interactively examine more detailed layers of data within a report. For example, you may be able to drill down into a national sales report to find:

  • What percentage of total sales did the Northeast region generate?
  • How much of Northeast sales revenue was generated by in-store sales?
  • Which Northeast stores generated the most revenue?

Drill-through reports are those opened by clicking on an item that then takes a person to another related report. Often, the drill-through report contains more details about an item listed in a summary report. For example, clicking on the name of a specific store opens a report about the store’s performance.

Why Is Data Drilling Important? Why Drill Your Data?

While all business reports can reveal upward or downward trends, data drilling helps businesses perform diagnostic analysis, or the process of understanding why trends and events happen. It enables you to view the data in different ways and explore related information that provides valuable context.

People across a business, whether they’re in sales, marketing, manufacturing or other department, can use data drilling to gain insights into their parts of the business. Data drilling is particularly useful because people generally don’t require any specialized technical knowledge to apply it. Data drilling also provides more flexibility and reduces redundancy by letting multiple managers explore the same dataset in different ways depending on their needs. And it makes analysis more widespread because you don’t have to be an expert in data science to drill down into reports and begin to identify trends.

What Are Drill Hierarchies?

A drill hierarchy defines the paths that people can use for data drilling within a report or spreadsheet. It is a predetermined set of data groupings at multiple levels, with the summary data at the top and progressively more detailed subgroups of data below. Drill hierarchies are often based on geographic regions or units of time. For example, descriptive analysis in a report might show ecommerce sales for the last month. To analyze the data in more detail, you could drill down through the hierarchy to examine sales for specific days, hours within each day and even minutes within each hour.

Benefits of Data Drilling

The main benefit of data drilling is to quickly provide better insights into the information in a report or spreadsheet. Understanding the cause of a trend enables decision-makers to quickly act on the data. For example, a consolidated sales report may show that overall sales are growing — but data drilling reveals that sales of some products are rising rapidly, while sales of other products are actually falling. Based on that analysis, the company can further investigate the causes and decide where to focus its resources.

Furthermore, data drilling delivers different points of view based on the same data. Managers and analysts can explore the data from different perspectives to gain a more thorough understanding of the underlying trends.

Limits of Data Drilling

Data drilling is limited by the way the data was originally entered and categorized, and by the paths defined by the drill hierarchy. Data drilling provides a predetermined number of ways to explore data, such as drilling up and down the hierarchy. A person can only drill down to the lowest level of detail defined in the hierarchy. To explore the data in other ways, businesses need to use other analysis techniques, such as machine learning.

Data quality can also limit the value of data drilling — as with any BI approach, data drilling is only useful if the underlying data is accurate and current.

Drilling Types

There are several types of data drilling, each referring to a different way to navigate through data. Here are the most common.

  • Drilling down involves navigating down through a hierarchy of information from the most general summary data to more specific data grouped at various sublevels. For example, in a report that lists the latest quarter’s total vehicle sales, a person might drill down to see sales of trucks and then drill down again to see sales of each truck model.

  • Drilling up is the opposite — moving up the drill hierarchy from a detailed view of a subgroup to a more consolidated view. For example, if a salesperson is currently viewing truck sales data, she could drill up to see total sales of all vehicles.

  • Drilling in, or drill-to-detail, provides more detail about a specific point on a chart or graph. Clicking on a point in a line graph showing the year’s sales might display the raw data for a specific month.

  • Drilling across or drilling through: Drilling across, also known as drilling through, links to a related report or other information outside the current report. Often, that report is generated by a different application. For example, if a salesperson is examining information about specific truck models in a sales report, he might then drill across to production data for the same model.

Drilling Use Cases

Every department in an organization can use data drilling to explore their data. Typical use cases involve drilling down to see more detail or the causes of trends.

  • Geographic analysis: In a general sales report, you can drill down from overall numbers to more specific revenues. A state-by-state report of sales revenues may allow you to select a particular state, click on it and then see sales revenues for each county or city in that state.
  • Time-based analysis: Alternatively, if the original data is date-based, you may drill through the data by drilling down from annual numbers to figures for each quarter, each month or each day.
  • Visualizations: Similar drill downs can be applied to visualizations. In a line graph, a person can click on points to uncover the data it represents (a 52-week high price, for example). If regional sales data is represented as a map, the person could click on a region to see the detailed underlying data.

How to Drill Up and Down

Drilling up and down are generally simple and intuitive operations, although the exact method varies depending on the software you’re using. Within reports, icons associated with each item indicate whether a person can drill down for more detail or drill up for an aggregated view. Some products allow users to view the entire drill hierarchy, so they can see all the levels of detail available in drill downs. Links indicate whether they can drill across to related reports.

Data drilling is one of the most fundamental and important business intelligence techniques. It’s simple to use and applicable to almost any kind of business data. By enabling businesses to explore information from different perspectives and at different levels, data drilling can provide fresh insights into trends. Data drilling helps businesses understand not only what is happening, but also why it is happening.

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Data Drilling FAQs

How does drill down work?

Users can drill down through a tabular report, worksheet or chart by moving down through a predetermined hierarchy of categories. For example, each line in a company’s sales report may list annual sales for a specific business group. Drilling down into that data may display sales for a specific month, weekly sales or day-to-day sales figures.

What are drill pathways?

Drill pathways, or drill maps, determine the options available for data drilling within a report. Typically, you can drill up or down a hierarchy of data categories using preset pathways — for example, you can drill down from national to regional and local data.

What visuals can be drilled?

A variety of visuals can be drilled, depending on the software you’re using. They typically include bar graphs, pie charts, bubble and leaf diagrams. Hovering over a particular graphic element will usually reveal whether it can be drilled. Drilling a graph typically displays detailed data for the selected element within the graph.

What do you mean by a drill through report?

A drill-through report is one that is also linked to another related report. For example, a report that lists mileage for all vehicle categories may link to a report detailing sales figures for pickup trucks.

Why do we have to drill down the data?

Drilling down through data is a quick way to better understand trends and important details in the data contained within a report. It can help companies understand the elements that are responsible for overall patterns within the data. For example, if the company’s manufacturing output slowed, drilling down may pinpoint the facilities or production lines responsible for the decrease.

What does drill down mean in accounting?

Data drilling is a business intelligence (BI) technique. It can help companies in various industries and any department — including accounting — that has data and reporting can use data drilling. It helps companies analyze information by providing different views of the data in reports, charts and spreadsheets. If a financial report shows a dramatic increase in revenue, you can drill down into the data to see what’s driving the sales. For example, a company that sells reusable products noticed a dramatic increase in revenue one quarter. After drilling down into the details, they found most of the increase was driven by the sale of reusable grocery bags after a law went into effect banning the use of plastic bags in stores.