Reporting – the first step to using the power of data

Everywhere we hear about the huge role of data in enterprises. Nowadays, information is considered a resource with a much greater strategic role and potential than petroleum once had. Data reporting is becoming more and more important. And without the right knowledge, tools or technology, both the data we collect and the petroleum extracted are not very useful. 

It’s rather obvious that humanity is far better at processing energy resources than terabytes of generated data. This is a shame, considering that virtually every enterprise has a wealth of useful data, but very few companies actually use this potential.

Each company can use a wide spectrum of data and do it effectively.  Just start with changes in the most fundamental and omnipresent process of working with data – reporting. The essence of reporting is the conversion of raw data into useful knowledge that is helpful both in controlling business processes and making decisions.

Transactional, financial, behavioral or marketing data can be processed and presented in countless ways. However, the real art is developing such an approach that will allow you to effectively obtain credible and up-to-date knowledge – which is not easy at all, especially if you’re not using appropriate tools …

Simple report not so simple after all

To better illustrate the challenges encountered in the reporting process, imagine what people working with data go through every day. The managerial staff asks for a new sales results report from the last quarter, which will take into account the division into product categories and individual days and months. The issue does not seem particularly demanding, so the analyst gets to work. However, building even such a basic report requires several steps:

  • Acquiring data from the appropriate source – CRM, data warehouse, files stored on the company’s server or in the cloud. Some systems allow fairly friendly exports, others may require certain skills – e.g. writing SQL queries.


  • Data quality verification – formats, missing records, consistency. In case of problems at the quality level, it is necessary to uniform or supplement the data with other sources. Or limit the scope of the conducted analysis. Unfortunately, all options are time-consuming.


  • Preparation of data using a suitable tool. If the analyst uses spreadsheets, he will have a lot of work to do with the appropriate setting of individual sheets, the introduction of appropriate formulas for aggregates in terms of product categories and time, and generating charts. A skilled user may prepare individual sheets and build a pivot table, which will reduce to some extent the work at the analysis stage. Creating the table, however, will take time.


  • Generating appropriate visualizations. A lot depends on the analyst’s “feel”, knowledge of good practices and limitations of the tool itself. Popular spreadsheets will allow you to use a defined range of visualizations. While basic charts are operated relatively conveniently, more advanced forms of presenting conclusions usually require a fairly good knowledge of the package used.


  • Sharing analysis results: the last step will require the analyst to transfer the generated visualizations to a presentation or text document and describe them accordingly. For many people working with data, this is the most tedious stage of the process. They often feel that they have to describe obvious conclusions.


Meanwhile, the managers came up with additional requests: as part of the report, they would like to see the sales results by region. Such requests certainly make sense and can help better understand the results. From an analyst’s perspective, however, it means repeating previous steps! It is always better to know the requirements at the very beginning of the analysis – that way you can save a lot of time and effort.

It is worth remembering, however, that rarely the entire scope of the analysis is precisely determined and unchanging. In principle, the essence of analysis is to gradually deepen it and supplement with other sources. Appearing dimensions should also be taken into account as part of the ongoing work. Is it possible to speed up the demanding report building process and adapt to dynamically changing requirements?

Rapid reporting with Tableau

The reporting process can be significantly shortened, simply by focusing on the value-adding aspect – working with properly prepared data. Use a Business Intelligence platform created for such tasks to minimize the need for data transfer or preparation!

Meet Tableau – a leading solution on the Business Intelligence market. Known for its invaluable convenience of use, it enables the user to automate the most tedious activities related to data analysis, such as:

  • each data import,
  • formatting data or
  • aggregate calculation.


Tableau was created to help users see and understand data. Once you connect Tableau to the data source, you can proceed to create interactive visualizations that you can then filter and develop. Tableau’s “Drag and Drop” functionality is probably the simplest and most intuitive feature used in data analysis software. Thanks to this, creating a report in Tableau takes…


…less than a minute!

The implementation of Tableau in your organization will ensure that analytics will always be connected to current data. Moreover, unrestricted data analysis and visualization will become the essence of your analysts’ work and reporting will become much easier.

In the time needed to build a simple spreadsheet report, a Tableau-using analyst will develop an automatically updated dashboard that the managers will benefit from for subsequent quarters. What is more, the company’s resources – previously devoted to simple tasks – can now be allocated to business development.

Let’s talk about implementing Tableau in your company – contact us!


Article by Mateusz Gemra.