Excel has been the essential data analytics tool for years. Even now it’s hard to imagine the daily work of analysts without Excel in the background. However, the development of data-science has led to transferring some of the functions to other, more efficient tools. In the past, this was mostly the case of data storage (databases, warehouses), or data processing (SQL, ETL). As the trend of the tool for visual data analytics has been evolving, specific tools have been designed for the data analysis and presentation – such as Tableau. This trend has also been followed by Microsoft who has focused on developing its flag product – Power BI. So how to ensure smooth operation of these tools? I will try to address this question in the below post.
In the left corner: Excel
The comparison between Excel and Tableau is like comparing apples to pears – they have something in common, and at the same time they significantly differ. Excel is a calculation sheet designed for all types of operations and calculations involving tabular data. It’s a very flexible tool and its basic functions are pretty straightforward to learn. It’s excellent in facilitating daily work and can serve as a notepad for analysts. If you need to quickly calculate or check something – Excel is your best friend. The problem comes when you need to further process your data.
First of all, Excel has limited data storage capabilities – it’s not intended for this purpose. The limit of 1 million rows can be insufficient for many applications. Its efficiency is another drawback. When you have larger amounts of data and calculations, the conversion of sheets might be time-consuming. This aspect, however, was resolved some time ago by developing databases and data warehouses, where Excel was used as a tool for data analysis and presentation.
This area has also proven not to be its primary functionality. The growing awareness of the importance of the visual data analysis has led to the development of the business intelligence tools. Their job is to convert data into information and convert information into conclusions and recommendations. They are much more efficient than Excel. Why? Because they have been designed for this purpose.
In summary, Excel is a flexible tool that can carry out the whole analytical process, from the data source, through data modelling, analysis, to visual presentation. However, each step of this process can be performed in a dedicated tool built for this purpose. This way you can optimize the entire process and benefit the most from the available technologies. If you want to use Excel only, you will need to accept its drawbacks – for example, the limited amount of data, performance, visual capabilities. Excel is limited in all of these aspects, which has led to the development of separate, dedicated tools.
In the right corner: Tableau
Excel has some more or less significant limitations in almost all aspects of the analytical processes. The same case is with business analytics and visual data presentation. Excel, a calculation sheet, was not designed to create analytical dashboards, even if some people use it for this purpose.
On the other hand, Tableau was made for this specific purpose, having the visual aspect of the data analysis as its priority. Its comprehensive capabilities allow business users and analysts to thoroughly explore data, and Tableau is much more efficient in this aspect. Microsoft has somehow proven the limited functionalities of Excel by developing a dedicated tool – Power BI – instead of upgrading Excel.
Another advantage of Tableau is its ability to work with large data sets. There are no limits in terms of the number of rows, and there is a wide range of possible data linking options. In addition, Tableau uses its own data format (hyper extracts), which enhances its performance.
A further advantage is the possibility of sharing dashboards by publishing them on the Tableau server. There is no need to send files, and you can be sure that all users will have access to one version of your dashboard – one version of truth. This also makes it possible to monitor and manage access, which is a key feature in handling sensitive data.
There are, of course, certain drawbacks of Tableau. Similar to Excel, it was not designed for the purpose of data transformation, and it has significant limitations in this area. Tableau has addressed this issue by developing its own ETL program: Tableau Prep. It gives you a much wider range of data modelling options and allows to export the data as extracts directly to Tableau.
Tableau cannot be used as a data collection tool. If you need to gather information from users, for example to complement a forecast – Tableau will not help, whereas Excel can do that. Especially when it is combined with Sharepoint to facilitate sharing and working on the same files.
The verdict: Tableau + Excel
Tableau and Excel are better as a team, rather than competitors. Excel serves as the analyst’s notebook and is a perfect tool for ad-hoc analysis and calculations. It’s fast, simple and easy to learn. On the other hand, Tableau is a high-tech tool for visual data analysis. If you want to achieve the best performance of the analytical process, you need to take into account the last step of presenting the results of the analysis. Tableau is a tool made for this purpose. Without this, your work might be meaningless.
Mateusz Karmalski Tableau Author
