A Comparison of Oracle Business Intelligence, Data Visualization, and Visual Analyzer

We recently authored The Role of Oracle Data Visualizer in the Modern Enterprise in which we had referred to both Data Visualization (DV) and Visual Analyzer (VA) as Data Visualizer.  This post addresses readers’ inquiries about the differences between DV and VA as well as a comparison to that of Oracle Business Intelligence (OBI).  The following sections provide details of the solutions for the OBI and DV/VA products as well as a matrix to compare each solution’s capabilities.  Finally, some use cases for DV/VA projects versus OBI will be outlined.

For the purposes of this post, OBI will be considered the parent solution for both on premise Oracle Business Intelligence solutions (including Enterprise Edition (OBIEE), Foundation Services (BIFS), and Standard Edition (OBSE)) as well as Business Intelligence Cloud Service (BICS). OBI is the platform thousands of Oracle customers have become familiar with to provide robust visualizations and dashboard solutions from nearly any data source.  While the on premise solutions are currently the most mature products, at some point in the future, BICS is expected to become the flagship product for Oracle at which time all features are expected to be available.

Likewise, DV/VA will be used to refer collectively to Visual Analyzer packaged with BICS (VA BICS), Visual Analyzer packaged with OBI 12c (VA 12c), Data Visualization Desktop (DVD), and Data Visualization Cloud Service (DVCS). VA was initially introduced as part of the BICS package, but has since become available as part of OBIEE 12c (the latest on premise version).  DVD was released early in 2016 as a stand-alone product that can be downloaded and installed on a local machine.  Recently, DVCS has been released as the cloud-based version of DVD.  All of these products offer similar data visualization capabilities as OBI but feature significant enhancements to the manner in which users interact with their data.  Compared to OBI, the interface is even more simplified and intuitive to use which is an accomplishment for Oracle considering how easy OBI is to use.  Reusable and business process-centric dashboards are available in DV/VA but are referred to as DV or VA Projects.  Perhaps the most powerful feature is the ability for users to mash up data from different sources (including Excel) to quickly gain insight they might have spent days or weeks manually assembling in Excel or Access.  These mashups can be used to create reusable DV/VA Projects that can be refreshed through new data loads in the source system and by uploading updated Excel spreadsheets into DV/VA.

While the six products mentioned can be grouped nicely into two categories, the following matrix outlines the differences between each product. The following sections will provide some commentary to some of the features.

Table 1

Table 1:  Product Capability Matrix

Advanced Analytics provides integrated statistical capabilities based on the R programming language and includes the following functions:

  • Trendline – This function provides a linear or exponential plot through noisy data to indicate a general pattern or direction for time series data. For instance, while there is a noisy fluctuation of revenue over these three years, a slowly increasing general trend can be detected by the Trendline plot:
Figure 1

Figure 1:  Trendline Analysis

 

  • Clusters – This function attempts to classify scattered data into related groups. Users are able to determine the number of clusters and other grouping attributes. For instance, these clusters were generated using Revenue versus Billed Quantity by Month:
Figure 2

Figure 2:  Cluster Analysis

 

  • Outliers – This function detects exceptions in the sample data. For instance, given the previous scatter plot, four outliers can be detected:
Figure 3

Figure 3:  Outlier Analysis

 

  • Regression – This function is similar to the Trendline function but correlates relationships between two measures and does not require a time series. This is often used to help create or determine forecasts. Using the previous Revenue versus Billed Quantity, the following Regression series can be detected:
Figure 4

Figure 4:  Regression Analysis

 

Insights provide users the ability to embed commentary within DV/VA projects (except for VA 12c). Users take a “snapshot” of their data at a certain intersection and make an Insight comment.  These Insights can then be associated with each other to tell a story about the data and then shared with others or assembled into a presentation.  For those readers familiar with the Hyperion Planning capabilities, Insights are analogous to Cell Comments.  OBI 12c (as well as 11g) offers the ability to write comments back to a relational table; however, this capability is not as flexible or robust as Insights and requires intervention by the BI support team to implement.

Figure 5

Figure 5:  Insights Assembled into a Story

 

Direct connections to a Relational Database Management System (RDBMS) such as an enterprise data warehouse are now possible using some of the DV/VA products. (For the purpose of this post, inserting a semantic or logical layer between the database and user is not considered a direct connection).  For the cloud-based versions (VA BICS and DVCS), only connections to other cloud databases are available while DVD allows users to connect to an on premise or cloud database.  This capability will typically be created and configured either by the IT support team or analysts familiar with the data model of the target data source as well as SQL concepts such as creating joins between relational tables.  (Direct connections using OBI are technically possible; however, they require the users to manually write the SQL to extract the data for their analysis).  Once these connections are created and the correct joins are configured between tables, users can further augment their data with data mashups.  VA 12c currently requires a Subject Area connected to a RDBMS to create projects.

Leveraging OLAP data sources such as Essbase is currently only available in OBI 12c (as well as 11g) and VA 12c. These data sources require that the OLAP cube be exposed as a Subject Area in the Presentation layer (in other words, no direct connection to OLAP data sources).  OBI is considered very mature and offers robust mechanisms for interacting with the cube, including the ability to use drillable hierarchical columns in Analysis.  VA 12c currently exposes a flattened list of hierarchical columns without a drillable hierarchical column.  As with direct connections, users are able to mashup their data with the cubes to create custom data models.

While the capabilities of the DV/VA product set are impressive, the solution currently lacks some key capabilities of OBI Analysis and Dashboards. A few of the most noticeable gaps between the capabilities of DV/VA and OBI Dashboards are the inability to:

  • Create the functional equivalent of Action Links which allows users to drill down or across from an Analysis
  • Schedule and/or deliver reports
  • Customize graphs, charts, and other data visualizations to the extent offered by OBI
  • Create Alerts which can perform conditionally-based actions such as pushing information to users
  • Use drillable hierarchical columns

At this time, OBI should continue to be used as the centerpiece for enterprise-wide analytical solutions that require complex dashboards and other capabilities. DV/VA will be more suited for analysts who need to unify discrete data sources in a repeatable and presentation-friendly format using DV/VA Projects.  As mentioned, DV/VA is even easier to use than OBI which makes it ideal for users who wish to have an analytics tool that rapidly allows them to pull together ad hoc analysis.  As was discussed in The Role of Oracle Data Visualizer in the Modern Enterprise, enterprises that are reaching for new game-changing analytic capabilities should give the DV/VA product set a thorough evaluation.  Oracle releases regular upgrades to the entire DV/VA product set, and we anticipate many of the noted gaps will be closed at some point in the future.

Using Data Visualization and Usability to enhance end user reporting – Part 4: Tying it all together

Now that the foundations have been set in my last three posts, in this final post I’ll share how we can create reports, leveraging:

• Standard definitions and metrics
• The understanding of how users  will consume data and interact with the system

To effectively create reports, make sure to follow these key best practices:

1. Reduce the data presented by focusing on the important information. For example, rather than showing two lines for revenue actuals and revenue budget, try showing one for the difference. Users can identify trends much more quickly when there are fewer objects to focus on.

2. Concentrate on important data and consolidate it into chunks. If you have two charts, use the same color for revenue on both of them. This makes it easier to interpret and see trends between them

3. Remove non-data items, especially the images, unnecessary lines and graphics. This helps the user focus on the actual data, so they can see trends and information rather than clutter.

Here is an example of two reports with the same data. The first provides a table with various colors, bold fonts and line. The second report highlights the important areas/regions. Your eyes are immediately drawn to those areas needing attention. Table two allows the user to draw accurate conclusions more effectively and in a much shorter timeframe.

These are some general practices which can be applied in most cases and will give users a much more positive experience with your reporting system. If you need help making sense of your reporting requirements, creating a coherent reporting strategy or implementing enterprise reporting, please contact us at info@ranzal.com.

Using Data Visualization and Usability to Enhance End User Reporting – Part 3: The Balance between Data and Visual Appeal

In part three of my blog series, I’ll provide an overview of the important balance between data and visual appeal when creating reports, including some of the latest research and findings.

Many users believe that once you have the metrics in place and understand what data users want, the next step is to create the reports.

In reality, a lot of thought and a careful eye are required when making design considerations to create charts, grids and tables that convey the details in the simplest terms for user understanding. The right design choices enable users to see easily the trend, outliers, or items needing attention.

Many people think that the more data they can cram in, the better. However, studies have shown that the average person can only store 6 chunks of information at a time.  Depending on how flashy and distracting your graphics and marketing logos are, you may have already used up half of your brain’s capacity, without getting to any reports or dashboards.

Graphic overload may make one consider removing all distracting graphics, highlights, bolds and visual clutter to show the data – novel concept right?

But this is not the solution. There has been lots of visualization studies and research done over the past century that have uncovered that eliminating graphics altogether is not the solution to this dilemma.

In fact, there are several leading experts on this topic, including three key people, who are leading the charge against clutter and visual distraction, cheering for more measured and thoughtful chart and dashboard visual design. These individuals are:

·         Edward R. Tufte

·         Colin Ware

·         Stephen Few

All three have published several books explaining how we interpret visual data, including what makes our eyes drawn to color and form, and what aids understanding. It also explains “chart junk” – a term first coined by Tufte in 1983. Tufte defines “chart junk” as simply:

Conventional graphic paraphernalia routinely added to every display that passes by: over-busy grid lines and excess ticks, redundant representations of the simplest data, the debris of computer plotting, and many of the devices generating design variation.”

The key concept of “chart junk” leads into another of Tufte’s mantras called the “Data Ink” ratio. The idea here is that by minimizing the non-data ink you are maximizing the data ink.  In other words,  that you can achieve the ideal balance of data and design by removing borders, underlines, shading and other ink elements which don’t convey any messages

There are a lot of available resources out there on this topic by these authors and others.

Stay tuned for my final blog post, in which I will demonstrate how to effectively put these concepts  into practice when creating reports.

Using Data Visualization and Usability to Enhance End User Reporting – Part 2: Usability

In this second part of my blog series, I’ll be looking at usability and what it really means for report design.

Usability takes a step back and looks at the interactions users have with reports. This includes how users actually use the reports, what they do next, and where they go. If users refer to another report to compare values or look at trends, they should think about condensing these reports into a single report or even create a dashboard report with key metrics. This way, users have a clear vision of what they need or what Oracle calls “actionable insight”. From there, users can provide other users with guided navigation paths based on where they actually go today.

With improved usability, users can review an initial report and easily pull up additional reports, possibly from a different system or by logging into the general ledger/order entry system to find the detail behind the values/volumes. With careful design, this functionality can be built into reporting and planning applications, to provide a single interface and simplify the user interactions.

Here is a real world example of how improved usability can benefit users on a daily basis: Often a user will open a web browser and an item is highlighted as a clickable link. Normally if you click on the link, it will open up in the same window, causing you to lose the original site that you visited. By clicking the back button, you can also lose the first site that you visited. With improved usability, clicking on a link would result in a new pop-up window, so when finished users are able to choose which windows to close and return to the original window.

The challenge with achieving improved usability, is that many organizations lack visibility into how users actually use reports, especially with users spread all over the world. One possible solution is for organizations to ask users about their daily activities. The issue here is that often users are uncomfortable discussing what they do and where they go online. Companies can overcome this challenge by enforcing sessions where they can ask leading questions including why users feel uncomfortable sharing their daily activities. These types of sessions can help organizations uncover the root causes/issues, giving them the insight to delve deeper to understand what lies behind the report request.

One common scenario where you could apply this approach is when users ask for a full P&L for their business units, so they can compare and ring anyone over budget.  By having a session to understand the users’ specific needs/daily activities, organizations can instead produce a dashboard that highlights the discrepancies by region. With this dashboard, there is no need to compare and analyze; users can open the dashboard and see the indicators with a click of a button. Users can drill down for more information while placing that call!

In conclusion, improved usability means helping users get to the answer quicker, without having to do a lot of unnecessary steps. The old adage is true – KISS – Keep It Simple Stupid!

Using Data Visualization and Usability to Enhance End User Reporting – Part 1: Introduction

Throughout my experience on client engagements, I’ve encountered a common issue: reports. In Part 1 of my blog I will address the reporting challenge, highlight some key benefits of standardized reporting, and outline an approach for implementing a standard enterprise reporting system.

On some engagements, clients want to reproduce the same old reports they had in the previous system, assuming that if users were complacent before, they would be happy with the same reports going forward. This is not the case. On a recent project, the client was in the midst of replacing a 10 year old system. Several business users were not happy at the prospect of continuing with reports that were created a decade ago!   Other clients think that because the finance team has been getting the same reports for the past few years, that’s all they need.  This is another incorrect assumption. In many cases these reports are not being utilized and users may even be using Excel to manipulate and turn the reports into something more useful.  So why would you give users the same old reports, when, with a bit of foresight and planning, you can give them reports which enhance the way they do business and actually make it easier for them?

Some of the key benefits of an enterprise reporting system are:

  • Single version of the truth – everyone has the same revenue /cogs/opex numbers
  • Analysts have more time to analyze data and trends rather than consolidate data to make reports

And how do you enhance reporting and deliver added value to users?

To provide users with the necessary reports, it actually takes a multi-disciplined approach, focusing on usability and data visualization.  This assumes you have created the back end databases with appropriate structures to support your reporting needs.   It’s also critical to have a single definition for accounts and key metrics. This makes a big difference in reporting and getting everyone aligned to the single version of the truth you are about to create.

In Part 2 of my blog, I’ll look at usability and what it actually means for report design.