Regardless of a company’s size, every business process should be accompanied by a meticulous data analysis and visualization.
Working with collected data, analysts face a lot of challenges: how to analyze it by aggregating, filtering and sorting. Presenting the data in the understandable form is crucial if you need to get business partners and coworkers interested in your data storytelling. Business reports prove to be the most suitable means for such a case.
But manual reporting doesn’t seem a perfect solution because it may slow down the analysis process greatly.
That’s why analysts need a tool which provides with a built-in reporting functionality and is ready to meet the upcoming demands of real-world situations.
The presence of the above-mentioned challenge leads us to the need for discussion of possible solutions. One of the BI tools that are worth to consider is a pivot table. Thus, it will be in the spotlight today.
We’ll talk about a pivot table as a centerpiece technology in data analysis, delve into its structure and give arguments in favor of using its web implementations. As a result, you will be well-guided in all the terminology to start creating reports right away.
What is a pivot table
A pivot table is a data analysis tool that transforms raw data into a summarized one. This technique helps to create powerful visualizations and derive
Structure & functionality
The structure is self-explanatory and intuitive: a pivot table is composed of three main areas to work with: rows, columns, and cells with aggregated values.
Think of each field of your data as a dimension. In the context of a pivot table, dimensions are presented as hierarchies. You can put them either into rows or columns.
Numerical hierarchies are interpreted as measures and can be put into cells. You can apply aggregation to them by using aggregation functions such as sum, average, maximum, minimum, and others.
Each cell contains an aggregated value at the intersection of a row and a column.
Each hierarchy contains members – values that belong to a field. They can be sorted or filtered by specified criteria.
Summarize the data using aggregation functions – there are 13 of them available in WebDataRocks. See them yourself:
Arrange the data right on the grid according to your business logic so it becomes easier to comprehend its meaning. For example, members can be sorted alphabetically/reversed alphabetically, aggregated values – in ascending/descending order.
- Filtering: Focus on the Important Data
We are guided by a ‘less is more’ principle. That’s why we recommend refining the data from irrelevant or redundant subsets of data. A pivot table offers
a filteringfor the records to concentrate only on the important information.
Three types of filters are at your service: based on values, member names and a special one – report filter.
- Slicing & Dicing
Do you want to take a look at your data from different perspectives? Change the slice dynamically by using a drag & drop feature. You spend a very little time to get a completely new view of your data. No need to ask the IT specialist to restructure your report – just drag & drop the necessary fields. This feature makes WebDataRocks a completely self-service tool.
See how slicing & dicing your data is easy?
Ways to look at the data
A modern pivot table should be flexible in all the senses. You may want to see a general picture from a bird’s eye view, or you may want to know details about a particular aspect of your data.
For this reason, hierarchies can be placed one after another or be in a multi-level (parent-child) form. Use operations like expand & collapse to the former and drilling down & up to the latter. These operations help you get an almost microscopic view of your data.
Whether you need an ad-hoc report or a recurring one, a pre-made functionality of a pivot table enables you to concentrate on the task itself rather than spending time thinking about how to do it technically.
Creating your first report in a pivot table
Now that you have a better sense of what the pivot table is, let’s get your hands dirty with practice.
At this stage, the most important thing is to ask yourself a question: “What do I want to achieve with this report?”.
Let’s create a quarterly sales report to gain insights about the most successful regions of sales.
Step 1: Add data to the table by selecting the fields as rows and columns. Here we’ve created a multi-level hierarchy to diversify our report.
Step 2: Choose the values you want to measure and apply the aggregation to them (e.g. the sum).
Step 3: Sort and filter the data.
Now that you see how our table became filled with meaningful data, filter it by selecting the top 5 best-selling countries.
Step 4: Finally, save your report locally in a JSON format by clicking the Save tab. Later, you can load it into the component and go back to editing it.
Moreover, you can export it to the most convenient format for you: PDF, Excel or HTML.
Now you have a web-based report that you can share with colleagues and friends.
Why a web pivot table is a first-rate choice
Considering the ubiquity of e-business and increasing volumes of data, taking advantage of existing online tools for analytics is essential for those who want to make their business flourish. Web pivot tables represent a perfect solution for handling this task. In contrast to their offline spreadsheet alternatives such as Excel, web-based reporting solutions definitely stand out due to:
- Customization options – you can make the component totally fit into the design of your application by changing its visual interface and functionality.
- Cross-browser compatibility & web responsiveness – you can run a pivot table and get access to reports from any device.
- Interactivity – you can change the data slice, aggregations, filters, and sortings on the fly.
- Integration options – whether you have a cloud-based application or a locally deployed one, you can embed a web-based pivot table in any project and provide your clients or employees with constant access to analytics.
- Sharing reports online – a built-in exporting functionality allows sharing results of the analysis between your colleagues.
Moreover, in WebDataRocks security of users’ data is our priority. We don’t collect or store your data on the server-side. Data is processed exclusively on the client-side and is stored only on your local or remote server.
Later, in a series of articles dedicated to challenges in various industries, we’ll take a closer look at real-world applications and learn how to solve analytical problems using WebDataRocks. Best practices will help you understand what is happening in your business, follow trends and make data-driven decisions significantly faster.