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By David Carr
Making data visual is a big part of making it understandable and useful. For all the excitement about novel data sources like social computing or the Internet of Things, data analysis will eventually flow into a report or dashboard where someone must make sense of it.
Reap the rewards of agile analytics in the cloud.
This requires time, tools, and judgment. While using the cloud for business intelligence does not on its own buy you better judgment, it may give you new tools and more time to focus on building clearer, sharper visualizations, according to Tim and Dan Vlamis, authors of Data Visualization for Oracle Business Intelligence 11g and principals of Vlamis Software Solutions.
“What's exciting is that the cloud allows a business to become more nimble and spend more time working on visualizations because someone else is taking care of the infrastructure,” Tim Vlamis says.
Instead of spending their time optimizing SQL queries or data warehouse configuration, BI developers can consider whether a bar, line, or pie graph is the best way to convey information, or when it makes sense to stick with a tabular presentation but use typography and white space to make data easier to scan. They can “put time and effort into making sure they are delivering an excellent experience for the users,” Tim Vlamis says.
Spend a little time on your data visualizations and you will tell a clearer story. Here are some best practices to follow, courtesy of Vlamis Software Solutions. (5 slides)
Use a dark color to help important information stand out. Here revenue and cost are muted colors while the profit bar is darker to help that key information pop.
Sort row and column names by values and not by alphabet. Then use a heat map to clearly show the relative contributions by product group and total revenue by sales office.
Use a stacked bar graph to easily compare the total revenue for each customer segment and then within that segment, revenue by gender. This is cleaner than including a separate bar for each value.
Light background colors can help group columns for easy interpretation and visual scanning.
As with other cloud software, cloud BI opens up possibilities for business users who want to bypass IT. Whether or not this is a good thing depends on whether the IT organization truly adds value—for example, by counseling business users on when cloud services are appropriate and steering them toward the best options, Tim Vlamis says.
Yet for any cloud service, the self-service option “is a key capability for business users who dread nothing more than going to IT,” says Holger Mueller, Constellation Research analyst.
Business users can also get away with a relatively unsophisticated approach to data architecture because analytics technologies are now so powerful, Mueller adds. Behind the scenes, a cloud service can use technologies like Hadoop, which make it possible to store very large volumes of information without users knowing in advance how they'll query it, rather than following traditional relational database practices. “We’re living in a world where technology, all of a sudden, can do more than the business can absorb,” he says.
As more business applications move into the cloud, business intelligence and analytics applications will naturally follow. If data originates in the cloud, it makes sense to analyze it there, too. Add to these another reason for doing analytics in the cloud: possible access to more advanced capabilities.
For example, Oracle Business Intelligence Cloud Service includes a couple of significant features that are not available in Oracle’s on-premises software—Visual Analyzer and a data mashup capability.
Visual Analyzer allows even nontechnical users to select a few data sets and generate what the software thinks is the best visualization for the relationships between those items. “It does a pretty good job,” Dan Vlamis says. “Does it always do what we would think is most optimal? No.” But as an exploration tool, it helps business users uncover patterns and understand their data better, he says.
Oracle has also improved its default visualizations by removing visual clutter, such as a decorative background gradient on a graph, that distracts from its informational content, Tim Vlamis says. Oracle Business Intelligence Cloud Service lets you upload your own data and add it to an analysis. For example, a government analyst can enrich a revenue-by-state analysis to adjust for population, where population data is not included in the data warehouse. The analyst could upload a spreadsheet of census data and visualize the results on a map.
Demonstrations of Visual Analyzer provoke some jealousy in the on-premises world. Everybody loves it, and they’re dying to have it.
—Tim Vlamis, Principal, Vlamis Software Solutions
“Could you lobby the IT folks to load that into their tables and map it?” asks Vlamis. “Sure, but this makes you more fleet of foot.” Business users get to the same sort of ad hoc analysis they might previously have done in spreadsheets, but with the help of more powerful analytics and visualization.
Demonstrations of Visual Analyzer provoke some jealousy in the on-premises world, Tim Vlamis says. “Everybody loves it, and they’re dying to have it.”
This is a recurring theme in cloud computing: advanced features tend to arrive in the cloud first. More than most of its competitors, Oracle has made a point of saying it will deliver the same technology in the cloud and as traditional enterprise software to maximize portability between the two. Even so, new features can be put into production more quickly in a cloud environment that Oracle controls.
By taking advantage of advanced features, as well as the freedom to focus on quality of analysis rather than database engineering, cloud users can deliver better BI.