Monthly Archives: May 2017

What Does Revenue Recognition Really Mean?

May 31, 2017

Author: Tony Tauro, Performance Architects

What does the term “revenue recognition” actually mean?

Companies sell things. The money that organizations get from selling things is called “revenue.” The question becomes at what point in the sales cycle does that money become revenue?  That’s when revenue is “recognized.”  Is it…

When the customer sends the company a signed Purchase Order (PO)?
When the goods are dispatched by the company?
When the goods are received by the customer?
When the customer sends in the payment?

The answer to all these questions is…maybe.

If you are selling to a customer with very bad credit, it is prudent to wait until the payment is received before you account for it as revenue. If the goods are particularly high value, you’d want to ensure the customer received them before accounting for the revenue. If the product has low availability, you want to wait until you’ve dispatched the goods before you recognize the revenue.

The date on which the revenue is recognized has huge implications, and there are stringent rules and guidelines around this. A famous example is how Apple recognized revenue from its phones sold through the carriers. The carriers would “subsidize” the iPhone for customers, and recover the difference over two years. The carriers, however, had to pay Apple the full price. Apple would get $650 in cash per iPhone right away, but had to recognize the revenue over 24 months. Savvy analysts learned early how this discrepancy between cash flow and revenue would affect the value of the company and made a killing on the stock market as a result.

Another example is Microsoft’s 2015 decision to change how it recognized license revenue from the sales of Windows 10 licenses. Instead of recognizing the entire license as revenue immediately (as it used to do), Microsoft decided to defer the recognition over the lifetime of the device to account for the cost of providing periodic support in the form of upgrades. The “lifetime” itself depended on the form factor, so a tablet could have a two-year lifetime while a PC could have a four-year lifetime. While this reduced the company’s revenue, investors recognized the change for what it was and did not punish the stock price.

Not all revenue recognition requirements are complex. Sometimes it is as simple as accounting for logistics (in other words, letting the real world catch up with the virtual world). If an order is received after your logistics company has picked up all deliveries for the day, then you may have to recognize the revenue the next (working) day. If the product must cross borders and there is customs processing (which can be unpredictable at times), then you must wait for an extra event which often is not electronically communicated to your application. Thus, you need a mechanism (like a form) for a user to enter the date manually. These cases are especially relevant when the dates span “periods” like a month-end, quarter-end or year-end.

Revenue recognition is a simple concept, and like typical accounting practices can get rather complicated. The exact rules and how they are implemented vary by industry and by organization. The key is to be aware of the basic principle and know to ask enough questions to gather a comprehensive set of requirements.


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

Three Big BI Market Drivers to Watch for The Rest of 2017 and Beyond

May 24, 2017

Author: Tony Tauro, Performance Architects

In 2017, we’ve seen an expansion of business intelligence’s (BI’s) scope, changes in consumption, and shifts in the roles of BI consumers and creators. Traditional and fundamental BI practices and processes, however, remain more important than ever.

As a result, the three major market drivers of BI trends so far in 2017 include:

  1. Get more from your data
  2. Do it faster and cheaper
  3. Make your data better

These are not mutually exclusive, but instead tend to reinforce each other and the general direction of BI trends.

1. Get more from your data

Data is just bytes (or even bits) till someone can process it into information. Ideally, all the data sitting in our data warehouses has already been processed into information…of course, there is always better information if only we could read the data correctly. Data discovery and visualization are currently the hot tools to help us achieve more complete and better analysis of our data.

These tools are especially relevant because of the advent of another hot trend: big data. An easy way to understand big data is to think of the progression from to-do list to contact list to spreadsheet to relational database, and try to fill in what comes next: a solution that can handle data sets that are too big for traditional databases. And we are seeing more and more of such data sets now.

Once upon a time, manual data entry was the primary way to build data sets. Now data is introduced to data storage solutions automatically. Transactions are mostly electronic, and we have sensors producing data as well. It’s no wonder that our datasets are doubling in size every 2-3 years!  Big data tools are getting more and more prominent as companies realize the need to harness the power of this data.

Data discovery at its core is about interacting with your data the way you would with a search engine: ask a question and get an answer. Unlike a search engine, your data discovery solution gives you an appropriate (contextual) answer, considering items such as your role and permissions inside your company.

Visualization is about…visualizing your data, but it’s also about moving beyond the traditional graphs and charts that have always been used for BI. If data discovery is like using a search engine, visualization is a little like Wolfram Alpha, where you can query on a general topic, get in-depth information and find answers to questions you did not even know to ask.

Essentially data discovery and visualization techniques and solutions allow the consumer to create and discover the information needed, which brings us to the next topic.

2. Do it faster and cheaper

Since the days when humans fought velociraptors to win the evolutionary wars, “business people” have fought “IT people” for control of the reporting and analysis (BI) environment. Actually, one of those two things is pure hyperbole, but that is not the point.

“Self-service BI,” while not a new concept, is getting more traction now. While a diverse group, “business people,” are getting more savvy with BI solutions. At the same time, BI environments are getting more complex, making it even more important to get architecture and processes right.

Self-service BI is the concept that BI can be centrally managed, while also allowing “business people” to create their own set of reports, charts, graphs: basically, have their own BI and let IT manage it, too.

The savvy reader will note that data discovery and visualization are also forms of self-service BI, though that is not what is usually implied in general usage of the term “self-service.”

3. Make your data better

Data discovery pushes the boundaries for how we source data, going beyond the limits of the traditional data warehouses and bringing in data from more and newer sources (hence the search engine analogy earlier). this introduces questions about how to control data quality and how to improve data context.

Sometime after the Dark Ages, we came to the realization that the shiniest of dashboards get their credibility from boring old data quality and master data management processes. Transactions (e.g., sales orders, invoices, material movements, accounting documents) are great. They represent action and contain numbers that can be put into reports (like financial statements) and (gasp) glorious visualizations! However, without tying back to master data, the transactions are just business data (not information), and certainly do not provide context.

Ultimately data quality and management is about ensuring that the consumers of the data have a solid set of assumptions to use while translating that data into information. Keeping those assumptions true in the light of growing data sets and sources is a challenge (or opportunity… which one is it?), but is essential for the data discovery, visualization and self-service capabilities to stay relevant.


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

How to Use the Row Expander Visualization Plugin with Oracle Data Visualization Desktop (DVD)

May 17, 2017

Author: Margaret Motsi, Performance Architects

One of the ways to enhance data visualization is by enabling a fully interactive drill up and down experience in the data hierarchy. Oracle’s Data Visualization Desktop (DVD) uses the
“Row Expander” custom visualization plugin, available at the Oracle Public Store, to offer the capability to dynamically drill up and down attributes that may not necessarily belong to a hierarchical column.  This means that a user can switch back and forth between summary and detail data to form intermediate subtotals and quickly analyze data.  This blog post provides instructions on how to get started with this plugin.

From the Oracle BI Public Store, find the “Row Expander Viz” plugin box and click to download.

This action will create the following notification:

Click the “Download” link and copy content into the “plugins” folder; if your installation doesn’t offer  “plugins” folder, simply create one. Additional plugins should also go into this folder.

Restart DVD. Once restarted, you can view the plugin in the visualization options.

Select desired columns and then right-click on “Pick Visualization.”

Select the “Row Expander” plugin

The attributes display as rows in the canvas along with the selected metrics. The default view shows the summary data.

You can click on each attribute to drill up/down to the next level.

You can also add or remove attributes as you go. The number of attributes is equal to the number of levels you can drill up and down.

You can also create a filter on an attribute by right-clicking the attribute and selecting “Create Filter.”

The plugin will filter accordingly.

You can drill up and down on the filtered data.

When it comes to measures, this first version of the plugin has a couple of limitations.  First, the plugin is only capable of performing the “Sum Aggregation” function on metric values. It will be able to perform other calculations in future releases of DVD.  Second, the input dataset is limited to 500 rows for the plugin to perform accurately.

Need help or advice on data visualization plugins?  Contact Performance Architects at sales@performancearchitects.com and we’d be happy to help.

 


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

Oracle Business Intelligence Enterprise Edition (OBIEE) RPD Management Changes in Version 11g Versus 12c

May 10, 2017

Author: Jordan Adams, Performance Architects

One of the first significant changes you will notice as a developer when upgrading from OBIEE 11g to 12c is RPD management capabilities, including uploading or downloading new or existing RPD models.  In the past, loads were always handled through Enterprise Manager (EM) and required a restart of the server when uploading a new RPD, but with a new tool called data-model-cmd, this is no longer necessary.

With this new functionality, we can run an “Upload a New RPD” or “Download the Existing RPD” command. In order to run these commands, first locate the tool on the server at <Oracle_Home>/user_projects/domains/bi/bitools/bin. The file extension depends on the environment you’re using. For Windows, the extension is “.cmd” and for UNIX it is “.sh.”

Next, write a command to execute one of the two scripts. When uploading an RPD, you need to specify the command “uploadrpd,” which is followed by a set of parameters for RPD location and name (you may also enter the password in this command, and if you do not you will be prompted for the RPD password upon execution); admin username/password; and the OBIEE server instance.  This is an example of the command:

<Oracle_Home>/user_projects/domains/bi/bitools/bin/data-model-cmd.sh uploadrpd -I home/rpd/New_RPD_Upload.rpd -W Admin123 -U weblogic -P Admin123 -SI ssi.  The difference when downloading the RPD is that you’re renaming the RPD to a name of your choice, and the parameter name is slightly altered to as follows: <Oracle_Home>/user_projects/domains/bi/bitools/bin/data-model-cmd.sh downloadrpd -O existing_model.rpd -W Admin123 -U weblogic -P Admin123 -SI ssi.

What are the benefits of these changes?  These changes allow developers an opportunity to make smaller changes and see the impact right away, without having to bring down the environment for all users.  Also, when uploading an RPD, it is much quicker, with one simple command which takes a few moments to complete.  Second, there’s no need to restart services to see changes to the model (unless you’re in “Presentation Services,” in which case you have to log out and back in to see the changes).

Need help with your OBIEE 11g to 12c upgrade?  The Performance Architects team has partnered with several clients on upgrade projects.  Please contact us at sales@performancearchitects.com and we would be happy to explore in more detail with you.


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.

How to Configure the Gantt Chart Plugin from Oracle’s BI Public Store for Oracle Data Visualization Desktop (DVD)

May 3, 2017

Author: Astha Patni, Performance Architects

Oracle’s Data Visualization Desktop (DVD) supports custom visualizations to satisfy the requirements of developers and end users. These plugins are available on Oracle’s BI Public Store. Within this website, Oracle provides a variety of data analysis and visualization plugins that can be installed on a user’s local client installation.  Once installed, these plugins are immediately visible within DV Desktop.

Oracle BI Public Store

In this example, we will add a new visualization called “Gantt Chart” into DV Desktop and demonstrate its features and options.  The Gantt chart visualization is a type of chart that illustrates the breakdown of a project into its tasks and sub-tasks. This chart illustrates the start, end, and duration of tasks within a project. The Gantt chart is one of most commonly used visualization to depict the timeline for tracking projects.

The process of installing the plugin begins by clicking on the “Gantt Chart” icon in the Oracle BI Public Store.  This will display a brief description of the plugin and a link to download the zip file.

After the download completes, the zip file is copied to a plugin directory under the user’s DV Desktop local application directory.   For example, for the Administrator user, the directory would be:

C:\Users\Administrator\AppData\Local\DVDesktop\plugins

Once the plugin zip file has been copied to the above directory, start or restart DV Desktop and the “Gantt Chart” visualization will be immediately available for use in new or existing DV Projects.

To demonstrate the Gantt chart, we will use a sample “Project Management” Excel sheet as a data source. The spreadsheet has information about the different projects implemented in an organization. Below is the sample data:

The first step is to import the data source into DVD. Create a new data source and browse the Excel spreadsheet using the “File” option.

Before accepting the data set, validate the data type of all the fields. In this case, “Resource” and “Cost” were coming as attributes, so they are changed to “Measure” for aggregation purposes. You can also change the metadata after import in case it is missed in this step. Click “OK” to accept the below data set.

Create a new project using the “Project Management” data source. Select these three fields: “Start Date,” “End Date” and “Project Name.”  It is important to select three fields including two dates and one attribute to prevent display issues with the “Gantt Chart” visualization.

The resulting visualization shows the attribute field spans across the start date and end date.  In this example, Project 1 is extended across the duration of 116 days, which the difference between the minimum start date of the task “Development” and the maximum end date of the task “Testing” against Project 1. Also, “Task” is not yet included in the chart so only a single bar can be seen against each project.

Add the metrics in the “Values” section. In the example below, the two metrics are “Resource” and “Cost.” Measures at the “Task” level as per the data set are summed up to the “Project” level. To show the summed-up value, metrics are identified with “**sum.”

Validation with the data source confirms that “Resources” involved in Project 1 are 37 and “Cost” is $44,000.

The only properties that can be changed on the “Gantt Chart” view are the major axis and minor axis. These can be changed to years, quarters, months, weeks, or days. Other properties are common to all the other visualizations like auto fit, canvas properties, etc.

Next add the “Task Name” to the “Color” section. This splits all of the projects into their respective tasks showing that each project has multiple tasks. Each task under a project is represented by a bar with metrics on it. For example, one of the bars for Project 1 shows “** sum” for the metrics as the same task “Development” has two rows in the datasource.

In conclusion, it can be useful to study the different type of visualizations available in the Oracle BI Public Store to determine which ones are best suited to view a certain data set. No complex configuration is required for these visual images, and these display the data in constructive ways.  It is worthwhile to have a weekly glance at the Oracle BI Public Store to be up-to-date on the different visualizations introduced in the Oracle BI world.


© Performance Architects, Inc. and Performance Architects Blog, 2006 - present. Unauthorized use and/or duplication of this material without express and written permission from this blog's author and/or owner is strictly prohibited. Excerpts and links may be used, provided that full and clear credit is given to Performance Architects, Inc. and Performance Architects Blog with appropriate and specific direction to the original content.