Sigma Computing is a robust cloud-based business intelligence and analytics platform that enables users to create, analyze, and visualize data in a collaborative environment. Sigma enables users of all skill levels to transform raw data into actionable insights. There are many ways data can be visualized within Sigma. The idea is that by choosing the right type of visualization, you will be able to garner real insights into the data trends and thereby make informed decisions through continuous improvements.
Workbooks in Sigma Computing are a way to organize your analysis and visualizations. Workbooks are considered digital files hosting multiple pages, much like a spreadsheet file in Excel or Google Sheets.
Pages are the individual tabs within a workbook. Like the tabs in a spreadsheet, each page can be used to show different views of your data.
Elements are the objects that you place on a workbook page.
Element types include:
You can have an element in your workbook act as a data source for another element. We'll refer to the source element as the parent and the element making use of the data as the child.
Visualization isn't just graphical elements to add oomph to an analysis; they add context to the data. They let you build, but more importantly, explore and view, your data in a more focused and digestible format. You would create each visualization to deliver specific data insights and answer key questions that will drive and empower better business decisions.
When choosing a chart, take a moment to think about what you are trying to convey about your data.
Different charts highlight different aspects. Here are some types of visualizations in Sigma.
A bar chart is a chart that depicts values of different categories using rectangular bars. It is very good at representing categorical data and depicting comparisons across groups. Bar charts are readable and an efficient way of summarizing big data. Bar charts are effective at showing comparisons in the size, frequency, or value of different categories or groups. The common types of bar charts include vertical, horizontal, stacked, and grouped; each has its fit for a particular need in visualization.
Below is an example of a column chart using the tool Sigma Computing.
The line graph represents data trends across continuous intervals. It's particularly useful in representing time series information. It is simple to understand and allows for easy comparison between several sets of data. General uses include the performance of sales, the fluctuation of stock prices, temperature changes, and traffic flow on a website. In general, line graphs can provide clear and detailed insight into trends found in data, hence finding broad applicability in business, science, and finance-oriented uses.
Below is an example of a line chart using the Sigma Computing tool.
Pie charts show the proportion of a whole, and they are useful for a simple and fast comparison among categories. In fact, pie charts work best when there is a limited number of distinct categories with large differences. Other examples of uses include market shares, distribution of the budget, survey results, and population composition. It is a statistical diagram in the form of a circle divided into slices to demonstrate the proportion of numbers. Each slice indicates a category or part of the whole, with the size of each slice corresponding to the proportion of that category relative to the total.
For instance, a pie chart can clearly present the share of different brands in the market.
Area charts represent the trend of data over time or in categories through showing filled areas underlines for the cumulative effect of values. They really excel at highlighting magnitude and multiple data comparisons simultaneously, so they are quite well-suited for illustrating various changes in financial data, environmental trends, sales figures, and population studies. It colours or shades the area under a line, drawing attention to the size of the values and focusing on their accumulated total.
Below is a sample of the area chart using the Sigma Computing tool.
A KPI chart serves as a graphical display of the most important measures against which to track organizational performance for improvement. It underlines the most critical indicators, based on which assessment of progress towards objectives and identification of improvement areas become easy. KPI charts immediately present complicated data in a simple and comprehensible manner so that all levels of stakeholders understand the performance trend and make competent decisions to ensure continuous improvement towards goal attainment. In Sigma, the KPI chart summarizes either the total value over a specified period, the comparison of that value over time, or measures it against a benchmark or target.
Below, you have an example of a KPI chart created using the Sigma Computing tool.
Now, some of the charts built in Sigma are as follows:
Charts are like visualization tools that make complex information simple and understandable. Charts allow comparing, finding trends, and showing visual proportions or relationships between items. A suitable type of chart removes ambiguity and gives an overview to present information better.
While specifying user requirements for the dashboard functionalities of Sigma Computing, focus on the following:
Sigma Computing is a cloud-native analytics platform designed for collaboration in real time. With Sigma Computing, users are accorded self-service, in which less technical users can independently create and surface insights from data. A strong module for data governance assures security and compliance, while interactive visualization extends data exploration and knowledge. All in all, Sigma Computing allows agile and efficient work with data analysis across modern businesses.
Best Practices to Get the Most Out of Sigma's Visualization Capabilities are
In the end, Sigma Computing stands tall to provide high-level computation and visualization of data. Sigma intuitively holds several powerful features in its design, making it a must-have for those intent on digging deep into their data. Transform your data into action with the power of Sigma. Whether quality monitoring, distribution analysis, or relationships, these sigma visualizations will help raise your level of understanding and productivity in data-driven environments.
For those who want to know more about the Sigma Computing Analytical Tool, refer to the Sigma Computing Documentation.
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