Data Presentation in Business Intelligence

Introduction

In last three articles (1, 2, and 3) of this series, we discussed the overall Business Intelligence system architecture, different components, and how ETL helps store source data in the required form, followed by how OLAP (CUBE) helps to process, aggregate, and store huge amount of data. In this article, we’ll discuss another part of the overall BI system architecture: information delivery. How can we visualize or deliver data to help business owners and other users in the community? You can help them to know business trends and usability of the system, including other benefits. In the next the part of this series, you’ll know more about information delivery and various ways to represent data to help business owners in decision making.

Importance of Data Presentation

With the basic understanding of Business Intelligence, we should know the importance of data presentation in information delivery and how useful it is for business users. After storing data in the required form, either in a data warehouse/data mart database or an OLAP cube, data can be showcased in certain forms that will become the source of required information for all BI users; this is known as Reports in the BI world. These Reports can be data reports, executive dashboards, or conference presentations.

Data Reports may have different types of layouts to present the data, such as Metrics, Chart, Funnel reports, animated representation of data, and so on. All these kinds of data layouts can be considered, based on the targeted audience.

All these reports may represent Key Performance Indicators (KPIs) to visualize/present the data. These KPIs are a type of performance measurement. An organization may use KPIs to evaluate its success or progress, or to evaluate the success/progress of a particular business in which it is engaged. This data presentation is the logical end point for any BI system and becomes the source of truth for decision makers.

Reporting Tools

A reporting tool is an interactive data exploration and visual presentation of data that is stored in a database or cube and can be achieved by using various available reporting tools; the selection of a reporting tool for your purpose is solely your discretion but with supporting facts like we discussed, some selection criteria for OLAP tools in the previous article. There is no thumb rule to adopt a reporting tool; I want to reiterate this fact that the identification and adoption of any BI tool is not a personal decision and can’t be finalized without thorough study. You need to refer to the previous articles of this series to know more about the reasons why this is important for the successful implementation of any BI system.

There are varieties of reporting tools available that can be useful to present data and deliver the information. Some of them that come with Business Intelligence suites are Microsoft SQL Server Reporting Services, Oracle Reports, IBM Congnos Report Studio, and MicroStrategy Reporting Suite. Some open source tools are BIRT, JasperReport, Pentaho, and few other available tools for reporting are Tableau, QlikView, and the like.

Reporting tools help to visualize data in multiple, interconnected ways by using data regions. You can display data organized in tables, matrices, or cross-tabs, expand/collapse groups, charts, gauges, indicators or KPIs, and maps, with the ability to nest charts in tables.

Types of Reports

Once we finalize the reporting tool, the next step is to select the report design and data display to present the data as information for the user community. We need to consider key factors to design any report; these factors are the structure and tone of the report, length of report, kinds of data to include (tables, figures, graphs, maps, or pictures), detail of information, data positioning in the report, and the most important: visual sophistication.

We can explore different types of reports while considering the preceding key factors and organizing data in a variety of ways to show the relationship of the general information to the detailed. We can put all the data in the report, but set it to be hidden until a user clicks to reveal details; this is a drilldown action. Data can be displayed in a data region, such as a table or chart, which is nested inside another data region, such as a table or matrix. Another way is display the data in a subreport that is completely contained within a main report. Or, you can put the detail data in drillthrough reports, separate reports that are displayed when a user clicks a link. We’ll explore those ideas next.

Drilldown Reports: A Drilldown report provides plus and minus icons on a text box; these icons enable users to hide and display items interactively. This is called a drilldown action. For a table or matrix, it shows or hides static rows and columns, or rows and columns that are associated with groups.

Drillthrough Reports: A Drillthrough report is a report that a user opens by clicking a link within another report. Drillthrough reports commonly contain details about an item that are contained in an original summary report.

Subreport: A Subreport is a report item that displays another report inside the body of a main report. Conceptually, a subreport in a report is similar to a frame in a Web page. It is used to embed a report within another report.

Nested Reports: A Nest report can nest one data region, such as a chart, inside another data region, such as a matrix, typically to display data summaries in a concise manner or to provide a visual display as well as a table or matrix display.

A report can apply to a specific type of report item, a layout design, or a solution design. A single report can have characteristics from more than one type; for example, a report can be, at the same time, a stand-alone report, a subreport referenced by a main report, the target of a drillthrough report in a different main report, and a drilldown report.

Data Sources for Reports

Reports can leverage stored data in databases in the form of DW or DM or a cube to display. Data can be exposed by using a data source and data sets property in any report. These data sources and data sets can be exposed only to one report or shared with multiple reports. Report definition is always independent with the data source and data set and can be managed separately.

Different types of reports allow you to anticipate different report properties, such as drillthrough actions, expand/collapse toggles, sort buttons, Tooltips, and the use of report parameters to enable report reader interactions. To control data display or user interaction, we can use report parameters that can be combined with expressions and provide the ability to customize how report data is filtered, grouped, and sorted.

Industry Trends in BI Reporting

Industry trends are changing rapidly and user expectations are also growing with respect to information delivery by a BI system. In the current data world, a user not only analyzes structured data but also wants quick information on top of huge, unstructured data. We need to adopt and support new trends to meet user objectives in a rapidly changing paradigm.

We are observing great change in data visualization; the initial visual data discovery releases from the big organizations like Microsoft, SAP, IBM, Microstrategy, SAS, and Oracle tended to have limited capabilities, but the gap is slowly closing. The specialty organizations and the heavyweights are trying to find the right balance between analysis and trusted data.

Another important trend is mobility. Initially, the mobility of information was “nice to have,” but now it is an absolutely essential component of any useful report. The first mobile BI products allowed users to look at data remotely on their tablets and mobile phones, and as devices improved, dashboards and other visual representations made it easier for people to access the information they needed in the format they desired.

Another new trend is to present enterprise-wide massive amounts of data (Big Data). Everyone is talking about big data, but in the business intelligence world it means one thing: Organizations are being overwhelmed by massive amounts of new information that they need to analyze quickly and accurately. In the current industry trend, unstructured data will be a big part of this change because the ability to look at information not stored in spreadsheets and databases is letting organizations analyze information that they couldn’t truly leverage a few years ago.

It’s always highly recommended that organizations should change their way of operating and align with industry trends for better results and use the best of technology in their own interest.

Summary

In this article, we discussed how data visualization plays an important role for the successful implementation of a BI system. We discussed various types of reports and the factors that help in decision making for designing and implementing any report. Overall Information delivery is the last layer for a BI system, but this is the data presentation layer that turns data in information. It helps a diverse user community leverage to present the information; otherwise, users won’t be in a good situation to make any decision.

Visualization techniques revolutionize modern business intelligence gathering

Data scientists and analysts love digging into the architecture of data to grasp its essence, exploring how it works and divining what secrets it may hold. For some expert users, the very complexity of the data is what provides the “thrill of the chase.” However, the average user wants data that’s easy to understand. Visualization has proven to be the best way to make this happen.

Why does visualization work so well?

Noah Iliinsky, data consultant and coauthor of Beautiful Visualization and Designing Data Visualizations, spoke at a LinkedIn Tech Talk about the reason visualization is so powerful for analytics. “It turns out that our eyes and our brains have very sophisticated software built into them for things like pattern recognition and detecting when there are pattern violations on a variety of factors in terms of position, skew, color, size, blur, shape, etc. They are called ‘pre-attentive properties’. We can detect very quickly when something is different or out of position. If you leverage these well, you can design things where you can get a lot of information into someone’s brain very easily and very quickly.”

Enterprises are demanding more visualization

Business users may not know the science behind the way their brains process data, but they know what works. Presentation is king. Distilling data into the essential intelligence that will inform business decisions is pointless if the resulting reports are visually opaque. According to a recent TDWI white paper on self-service BI, “For information consumers, the results need to be easier to consume and use, and the solution here is to employ more sophisticated visualization techniques. These vary considerably, from using technologies such as Google Maps to display location-specific data, to visualization approaches such as small multiples, scatter plots, heat maps, enclosure diagrams, node links, arc diagrams, and more. Advanced visualization ranked third highest in the survey for enhanced user interface requirements, with 41% of respondents saying this was a ‘very important’ requirement.”

Tools must match the source, complexity, and variety of data

Being able to look at the same data in many different ways is critical since each perspective can add depth. The data visualization tools of the past, with their two-dimensional pie and bar charts, simply aren’t refined enough to offer real insight into complex data sets. Imagine trying to track the proliferation of power stations across the United States over time using a traditional Excel spreadsheet and a set of static graphs or charts. Assuming you have the relevant information stored on your SQL server, you could sort and present the data by date of initial operation, by state, by county, by power station type, and so on.

It turns out that our eyes and our brains have very sophisticated software built into them for things like pattern recognition.
Noah Iliinsky,
coauthor of Beautiful Visualization
However, making sense of the data really requires a map—and some way to visually express the changes that are taking place over time. The new “GeoFlow” visualization tool from Microsoft is a good example of how geographic data can be viewed in a way that permits the eye to easily detect patterns. It also includes the ability to drill down into the data after the overall trends become apparent so that users can uncover additional intelligence.

More features of a smart enterprise BI tool

Beyond offering many ways to present BI, the right solution will also give users more control over reporting. While visuals are important, they shouldn’t distract from the data or from business objectives. Every feature should be easy to use and fill a functional role. Here are a few key features that make a difference:

1. Interactivity, especially the ability to slice and dice the data
2. Full OLAP support
3. Static and dynamic capabilities
4. Visuals that relate to the real world within which the business operates
5. Multidimensional analysis
6. Collaboration for team analytics
7. Real time or near real time capability for live BI needs
8. Meta-visualization in dashboards

Visualization is about more than individual reports designed for distinct purposes or for certain departments. Dr. Joseph Morabito, Industry Associate Professor at the Stevens Institute, maintained in his 2012 talk about Big Data that different users require different types of visualization in terms of dashboards.

“The strategic dashboard is focused on high-level measures of performance. Typically, they feature static snapshots of data on a daily, weekly, or monthly basis, and there is little user interaction. You don’t want too much here. It’s better to be simple. Analytical displays are designed for detailed data analysis. Here, you’re going to have comparatively more data (and more complex data) but richer comparisons. You’ll have extensive historical data, but still mostly periodic snapshots. You’ll have a lot of interaction here with many OLAP features. Operational data requires a dynamic environment where we are using real-time or near real-time data (as in monitoring a supply chain management system). Here we need to keep it simple, as we do with the executive dashboard, but for different reasons. We need to see problems right away and then drill on demand so we can locate problems as they arise in real time.”

In the final analysis, users want more than BI solutions that enable them to achieve goals in their business. They want tools that make them feel smart. That’s the kind of positive reinforcement that provides the motivation leading to innovation. A data visualization solution that is versatile, well-rounded, and accessible for self-service is the best BI tool for this purpose.