Ever since the first digital spreadsheets were introduced in the 1960s, businesses have used them wherever they could. Quick access and simplicity have made spreadsheet software like Microsoft Excel and Google Sheets an important tool for marketers. Spreadsheets have been used for ages, but have in recent years proven to be ineffective in some cases. Cloud data warehousing technology is considered an alternative to spreadsheets when it comes to handling larger datasets. In this blog post, we explain how spreadsheets and marketing data warehouses are the best tools for different jobs.
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The benefits of spreadsheets in marketing
Spreadsheets are all about simplicity. The data is presented in a simple, tabulated form. Users don’t need to run queries to get the data, what they see is what they get. Basic data can be operated on using formulas that are based on basic math. More advanced functions such as VLOOKUP help users to analyze data across workbooks.
Getting started is very easy, as tools such as Google Sheets are practically free. Data sources for Google Sheets are vast, as you can basically copy-paste data from anywhere into a spreadsheet. Some tools even offer exports in the form of a spreadsheet file. If those are not available, tools such as Supermetrics can help you get data from various different platforms. Just install an add-on to your spreadsheet software and you can automatically pull data into your spreadsheets.
Spreadsheets are available on almost every computer in the world, which makes them instantly sharable. The file sizes are often small enough to be emailed to anyone. More modern spreadsheet software allows sharing spreadsheets to anyone with an email address. Better yet, some even allow for multiple people to work on one spreadsheet concurrently.
Where can data warehousing help?
Data warehouses are complex systems created for analyzing large sets of data. They come powered with a large amount of storage capability. Marketing data warehouses work as a single destination for all marketing data and they come equipped with powerful computing capabilities. Data warehouse users can perform more complex queries, as data warehousing platforms offer more computing power than a normal laptop would. As the datasets have increased in size, so too have the requirements for computing power increased.
As data warehouses contain more storage space, users can easily store data extracted from different sources. Not only that, but the data can also be from a larger time frame. Marketers can easily use historical data to do their analysis. For building reports, users of a data warehouse have the luxury of choice. Various business intelligence and reporting tools, such as Google Data Studio and Looker, can be easily connected to data warehouses. Using the power of the data warehouse, business intelligence tools can produce reports within seconds.
Data warehouses can take a bit more time to get started. In order to get the warehouse filled with data, it requires identifying data sources and creating transfers. However, building a data warehouse is much simpler now. Users can set up their Google BigQuery projects with just a few clicks. Configuring transfers requires some work, yet they are guided processes. While the setup can take time, most of the transfer can be just left running. Users don’t need to fix the transfers, as managed pipelines take care of any changes happening with the API connection.
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Spreadsheets and data warehouses compared
As spreadsheets and data warehouses have different approaches to data handling, they are suitable for different scenarios.
Spreadsheets work the best for simpler sets of data. Data contained is often compiled from a handful of data sources. Timeframe is usually limited to days or weeks. Users are using this data to form simple reports, usually with the graphs offered in spreadsheeting software. Some users might opt for building a report in Google Data Studio. Most of the time these reports are produced on an ad-hoc basis. Users need to have results fast to answer a question immediately. Spreadsheets work the best when used for quick reporting on a smaller scale.
Data warehousing works best when working with multiple data sources. The higher data volume requires more storage, but data warehousing is scalable to user needs. The volume of data is richer because of multiple sources being extracted and enhanced with historical data. Using multiple sources and historical data allows deeper reports that helps measure performance across different channels. Data warehousing takes a bit more time to set up. However, the setup time is justified by the purpose of building a sustainable reporting environment. Data warehousing works best for creating a data environment that is used regularly on a larger scale.
In the end, the question isn’t either or. Spreadsheets and marketing data warehouses are tools built for different purposes. Spreadsheets are the best when doing ad-hoc analysis on a smaller dataset. Marketing data warehouses are best for analyzing a large amount of data extracted from multiple sources. When used concurrently, they can be a powerful stack for data-driven marketers to work with. Supermetrics offers solutions for both spreadsheets and data warehousing products. To test them out, sign up for a free trial of Supermetrics for Google Sheets and Supermetrics for BigQuery.
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