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Tuesday, March 29, 2011

Magic Quadrant for Corporate Performance Management Suites 2011

Analyst research firm Gartner has published a new report titled " Magic Quadrant for Corporate Performance Management Suites", (Gartner RAS Core Research Note G00210145), dated March 8, 2011, authored by Neil Chandler and John E. Van Decker.

Oracle has been ranked the highest along the "Ability to Execute" dimension, and the second highest along the "Complete of Vision" dimension.

Some excerpts from the research note:
For more head over to the Gartner link above, or to the EPM and BI site at Oracle.com

New Oracle University Course: BI 11g Sys Admin

Oracle University has published a new online Oracle BI EE 11g course, "Oracle BI 11g R1: Introduction to System Administration - Online Course". It is in a self-study format, and is intended to allow users to learn how to manage Oracle BI 11g:
  • Fusion Middleware (FMW) Control to monitor manage, and configure Oracle BI system components
  • Oracle WebLogic Server (WLS) Administration Console to monitor and manage Oracle BI JEE Java components
  • Oracle Process Manager and Notification Server (OPMN) Tool to manage Oracle BI system components
  • Oracle BI Administration Tool to perform administrative tasks.
The course topics are:
  • Oracle BI System Administration Overview
  • Managing Oracle Business Intelligence
  • Configuring the Oracle BI SystemStarting and Stopping Oracle BI
  • Scaling an Oracle BI Deployment
  • Deploying Oracle BI For High Availability
  • Managing Performance Tuning and Query Caching
  • Diagnosing and Resolving Issues in Oracle BI
  • Managing Usage Tracking
  • Oracle BI Security

Thursday, March 03, 2011

Flash demo on Location Intelligence in Oracle BI EE 11g

There is a short, self-running Flash demo on Location Intelligence using Map Views in Oracle BI 11g.
Watch it here.

Map Views allow you to overlay analytics data over geo-spatial map using a variety of formats, like color-fills, bar graphs, pie graphs, bubbles, variable markers, and even images. 

As you drill from one level to the next, the formats carry over - which I think is very, very neat.

Tuesday, February 22, 2011

New BI Foundation Blog

Headsup - there is a new blog, http://blogs.oracle.com/bifoundation/ by the BI Foundation product management team. The first post, by the redoubtable Bob Ertl, is a promising peek into the kind of useful and informative stuff to expect in the days to come - Oracle BI Server Modeling, Part 1- Designing a Query Factory

Monday, January 31, 2011

Gartner Magic Quadrant for BI Platforms 2011

Gartner, a well-recognized information technology research and advisory company, published its Magic Quadrant for Business Intelligence Platforms (link to Oracle reprint, this is the permanent link) for 2011, Gartner RAS Core Research Note G00210036, authored by Rita L. Sallam, James Richardson, John Hagerty, and Bill Hostmann.

Oracle, unsurprisingly, continues to be positioned in the "Leaders Quadrant", for the fifth year running.

Here are some excerpts from the Gartner Research Note (emphasis mine):
Oracle customers indicate they deploy the Oracle Business Intelligence Suite Enterprise Edition (OBIEE) platform to support among the most complex deployments in our survey. Their scope of deployments tends to be the widest across an enterprise — regionally/nationally and globally deployed versus in a single or multiple departments — while OBIEE supports, on average, among the largest numbers of users, the highest data volume, broadest product functionality use, and highest complexity of analytic workload.

Oracle's OBIEE platform is considered the BI standard in more of its customers' organizations (survey respondents) than any other vendor's platform (considered a standard in 85% of their organizations compared to the survey average of 56%).

Some links on Oracle BI:
Oracle.com/bi
Business Intelligence Foundation
Enterprise Performance Management
BI Publisher
Essbase

Monday, January 24, 2011

Oracle Business Intelligence: Condensed Guide to Analysis and Reporting

Oracle Business Intelligence: The Condensed Guide to Analysis and Reporting Oracle Business Intelligence: The Condensed Guide to Analysis and Reporting

I was approached in December (2010) by Packt Publishing and asked if I would be interested in reviewing this book. I agreed, and the publishers provided me with a PDF version of the title.
This is a quick primer to the world of Oracle’s Business Intelligence Standard Edition products like Discoverer, Reports, Spreadsheet Add-in, and to Oracle Warehouse Builder. It is clear that the author knows his subject area well, and uses a number of examples to illustrate such concepts as dimensions, data cubes, metadata construction, and working with Oracle Warehouse Builder to create target structures such as cubes and dimensions. For those familiar with these products however, there may not be much that is new. Those looking for information on the 11g version of these products will be disappointed as the focus is on the 10g version.

The first chapter, “Getting Business Information from Data”, provides the reader with a definition and description of the world of analytics, business intelligence, multi-dimensional data structures.

Chapter 2 introduces the user to the different components of Oracle Business Intelligence. The installation examples and screenshots use the 10g version. A simple installation scenario is described, where the user installs Discoverer without associating it to a metadata repository or identity management infrastructure which would give it access to public connections, portlets, and more.

Chapter 3 introduces us to analytical SQL functions, and there is a comprehensive example using the Oracle Database ROLLUP and CUBE functions.

Chapter 4 takes a closer look at the Discoverer Administrator, the admin tool used to create and manage Discoverer metadata, the EUL (End User Layer).

Chapter 5, “Warehousing for Analysis and Reporting”, is in my opinion by far the best chapter in the book, where the author dives into Oracle Warehouse Builder to give a very good and quick overview of how to create dimensions and cubes from data sources, and how to populate these cubes via staging tables. While the whole area of ETL (Extract, Transform, Load) is too large to be done justice in a single chapter, the author is able to do a commendable job of letting the reader take a glimpse into the powerful world of the product and the world of data warehousing itself.

The last three chapters, 6, 7, and 8, cover very commonly used and powerful Discoverer features like Drilling, Pivoting, Parameters, sorting, and conditional (or stoplight) formatting.

Some other, minor, quibbles with the book:. Diagrams are not labeled, making it difficult to refer to them except by the page numbers on which they appear.
. In the discussion of Oracle OLAP data in Ch 2, while analysts or data architects can certainly use Oracle Warehouse Builder, a much more suitable tool would be the Analytical Worksapce Manager (or AWM as it is commonly referred to.)
. There is no mention of Oracle BI Publisher and its integration with Discoverer. This was released in the second half of 2007, and allows users to use BI Publisher to create highly formatted report templates using Microsoft Word that use Discoverer worksheets as their data source. The advantage that this integration brings to the thousands of Discoverer customers is two-fold: they can create highly formatted reports from their underlying Discoverer worksheets, something that the Discoverer product does not allow users to do (basic formatting capabilities notwithstanding), and secondly, the ability to schedule and distribute such reports via email as attachments (PDF, RTF, HTML, etc...). This also has been a much-requested feature by Discoverer customers, and fulfilled a long-standing gap in the product.

In summary, there is much to like in the book. This book does do what the title says, viz., provide a condensed summary of Oracle Business Intelligence Standard Edition. While the book also covers in more generality such topics as dimensions, cubes, and data warehousing concepts, the treatment is at much too a high-level to be really useful. Two shortcomings prevent the from realizing its potential of becoming a truly awesome condensed guide to Oracle Business Intelligence:
. The organization of the chapters. The book seems to jump from one topic to another without giving much of a sense of cohesion, and it is not till the second half of the book when there is a logical flow to the content matter.
. The absence of a single dataset that would be used throughout the book as an example. That way a reader could follow the examples in a more coherent manner. Making a data set available for download to the book reader would have helped. The author could also have chosen to use an existing sample data set from the Oracle web site (ahem - yours truly had played a substantial part in the creation of the SH dataset).

The best book on Discoverer 10g, in my opinion, still remains Michael Armstrong-Smiths’s Discoverer 10g Handbook. It’s a pity Michael has not yet published an updated version of the book, since there is a lot that has changed in the 11g release with respect to how Discoverer is installed, managed via Oracle Weblogic and the new Enterprise Manager console. Then there is the integration with BI Publisher, the migration utility for migrating your EUL-based Discoverer metadata to the Oracle BI Server RPD-based metadata. There is also a workbook migration utility that is on the product roadmap, as is further integration with the Dashboards product in the Oracle BI Suite Enterprise Edition.

Oracle Business Intelligence: The Condensed Guide to Analysis and Reporting
Oracle Essbase 9 Implementation Guide
Oracle Warehouse Builder 11g: Getting Started
The Business Analyst's Guide to Oracle Hyperion Interactive Reporting 11

Oracle Business Intelligence: The Condensed Guide to Analysis and Reporting Oracle Essbase 9 Implementation Guide Oracle Warehouse Builder 11g: Getting Started The Business Analyst's Guide to Oracle Hyperion Interactive Reporting 11

Kindle for the Web - Discoverer 10g Handbook



Kindle for the Web - Hyperion Planning



Kindle for the Web - Oracle Data Warehousing and Business Intelligence

Monday, October 25, 2010

Replay of eseminar - Visualizations in OBIEE 11g

An eseminar on visualizations in Oracle BI EE 11g that I did in September is now available on Oracle University (http://ilearning.oracle.com/) at eSeminarOracle BI EE 11g - Visualizations

Replay of spatial visualizations in OBIEE 11g

As I posted I did a webcast on spatial visualizations in Oracle BI EE 11g (Spatial Data Visualizations in OBIEE 11g). This eseminar is now available online at eSeminarOracle BI EE 11g - Spatial Visualizations - this may require a login and may not be available free for everyone.

Monday, October 11, 2010

Spatial Data Visualizations in OBIEE 11g

I did a webcast last week on spatial data visualizations in Oracle BI EE 11g. This entire session was focused on mapping in the suite, and while I tried to split the time evenly between the front end and the back end parts of mapping, I realize that talking about and explaining how the magic actually happens requires more than 20 minutes or so.
The plan was to do a very quick introduction to maps in 11g, and then dive straight into demonstrations. I have followed this path frequently in the last - start off at the top, show the capabilities of the product in the Dashboards interface, as end-users would see it. In most deployments, your dashboarding product is seen by more than 90% of the users. Then move to Answers, the report creation  and analysis interface. Often also known as the "power user interface", this is where analysts will often go to to perform deep analysis using the tools at their disposal. Answers is also the product that is used to create the analyses - tables, pivots, graphs, maps, gauges, etc... - that are published to a Dashboard page.
The point of starting out with a Dashboards demo is to show how easy to use the interface in maps is for end-users, and the great number of options available to them, from sliders on color ramps, to drilling, to invoking Actions, to sending master events to listening views, to checking on or off different formats displayed on a map, and more.
After this little bit of magic is shown to the user, the focus then shifts to Answers. Here the point is a little different, and yet much the same too. To show how easy it is to create reports with maps. That maps are really just another view in the product suite. A point-and-click interface is what drives the creation of maps. That it is possible to create maps in as little as 15 seconds. Or less.

As we move further down the rabbit hole, we come to the little piece of magic that actually creates the maps. But before that, I explain that placing analytics data on a map is really no different than fetching a column of data from another table. Which is what you do when you write SQL statements that use foreign key joins. Maps are no different. You need to fetch the spatial attributes of a geographical column. The spatial attributes often reside in a table in a column of data type sdo_geometry, while the rest of the information is coming from your analytics warehouse. What makes it possible to have MapViewer display non-spatial information along with spatial information is the Non-Spatial-Data-Provider plug-in mechanism. Read MapViewer Concepts fro the Oracle® Fusion Middleware User's Guide for Oracle MapViewer 11g Release 1 (11.1.1) Part Number E10145-04

 Towards the end of the session, I had this neat little slide that I borrowed from one of David Lapp's excellent presentations, that I think captures very neatly the four main scenarios of mapping in an analytics environment. 

Tuesday, September 28, 2010

Data Visualizations - Show Some Hide Some

The Search Engine Land site had a post on Jun 29 2009 - Google: We’re Not Really That Big But If We Are, We Aren’t Bad - where charts were used; specifically, charts that Google has used to argue that while it may appear to be a big company, it is not that big when compared to some of its peers, or in relation to the size of the market itself.

Here is the data table used below (from the site):


And two pie-charts:


Let's start with the Google pie chart, which tries to highlight the diminutiveness of Google's market share.
Data visualization experts have lamented the use of pie charts in visualizing data. I will not belabor the point. Instead, I believe the same data could have been displayed more effectively using either of the two charts below

The first one is a simple vertical bar chart, while the second one is a stacked percentage vertical-bar chart. Since we are working with percentages, either chart is conveying the same information.

The data in question for Google is called out by the use of a different color, and the size of the data is made clear by the height of the 'Offline' bar. Even in comparison to the 'Other Offline' bar, the Google bar's size pales in comparison.
Adding a data label may seem redundant, but if the chart does not support hover tooltips, then adding the label, with the precise value of the series, helps.
OR


http://www.businessinsider.com/chart-of-the-day-google-is-not-that-big-after-all-2009-7 mentions the post, and has an accompanying chart:

Here the attempt is to compare each company on two variables - revenue and employees. A dual-Y-axis bar as the one used above is not good, not good at all, for such a presentation of data. What exactly is the point of plotting revenue and employees as bars in this graph?A line-bar maybe, but even that is sub-optimal IMO.

If you have to do this type of a comparison, the scatter plot is most effective since it allows for a meaningful comparison across companies too. To make this interesting, you could also add a third variable, and plot the data as a bubble chart. You could also use a butterfly graph.

When displayed as a vertical bar, what is obvious is that Google has much lower revenue, and even fewer employees when compared to any of the companies it is being compared with. Fair enough. But what the chart does display, but not tell you very clearly, is something very interesting, that I explain with charts below.

Take revenue and employees, the two measures in the chart above. To perform a meaningful comparison, it is first necessary to normalize these values first. One way is by using ratios instead. i.e., the ratio of the company's revenue to the number of employees. Divide the revenue by the employees, plot **that** data instead, and this is what you get:

Innaresting, wouldn't you say?
Google's per-employee-revenue is more than one million dollars (say it Dr Evil style and it doesn't sound as sinister, maybe funnier), while IBM is less than a fourth as much at $254k per-employee, and even Microsoft is only $600k per-employee.

What this tells us, as long a we are comparing these companies, is that Google is able to eke out a lot more revenue from its employees than other companies. Unless its employees are super, super-freaks, it can mean, among other things, that Google has achieved economies of scale far beyond its peers, like Microsoft, IBM, AT &T, and Verizon. In some ways it can also be an apples to oranges comparison, because the businesses that Google and ATT and Verizon and IBM are not exactly comparable. But, this is the set of companies that accompanies the post, and is also the set of companies that Google chose. So there.

If you were to do a similar comparison with Microsoft, taking only its Windows and Office divisions, that have a near-monopoly market share in their respective segments, I am sure you would come up with near-Google numbers, or maybe even better. Conjecture, but a fascinating one, IMO.

If you accept Google's proposition that the other companies in the comparison are in similar businesses as Google, or that they are competitors to Google, then you also have to accept the proposition that revenue-per-employee figures also should be similar. If they are not, it could be because the companies are diverisified into areas where such economies of scale do not apply; which is a fair argument to make, or that these companies are just not able to extract as much money as Google is.

Let's use another ratio. This time, I use market cap-to-number-of-employees as the ratio.

Why use this ratio? What does this tell us, if anything? Well, for one, market caps are fairly fickle numbers, and can be misleading. But since the data is from the Google table, let's use it anyway. What it may tell us is how valuable each employee is to Google's shareholders.

Simplistically speaking, each Google employee adds $5 million to the company's market capitalization.
That is more than twice Microsoft's.
That is more than sixteen times IBM's.
 
Again, assuming Google's employees are not all hyper-efficient Einsteins, and some or even many would argue that is indeed the case, it means at the very least that Google's hold on the business and industry it operates in is a lot more efficient and powerful than its competitors. Which could result from, among other things, near-monopoly pricing power.

 Let us use a third set of metrics, and this time, let's also plot a bubble chart, that can display three measures reasonably well.

What is plotted on the x-axis is market cap as a multiple of revenue. i.e. for Microsoft, the bubble in blue, this would be 184 billion (its market cap) divided by 60 billion (its revenues), to yield a figure of 3.07. And similarly for the others.
What is plotted on the y-axis is market cap as a multiple of operating profits.
The size of the bubble is the company's revenues.

What does this chart tell us?
Firstly, that Google plots as an outlier. Good outlier or bad outlier? Well, that depends on whether you are Google or its competitor.
It also tells us that Google's price-earnings ratio is way out of whack with its competitors. It could also mean that Google is incredibly over-priced, or that it has such a strangle-hold on its business that giant gains in market share, and consequently revenues and margins, are almost guaranteed over the coming years, which is why the market has driven up its market cap to such heights.

From Google's perspective, unless it intends using the currency of its market cap to make big-ticket acquisitions, such a high market cap is not really that good. It only attracts market envy and unwanted regulatory attention.

Anyway, another example of how data can be used to show some and hide some.

Wednesday, September 22, 2010

BI Applications 7.9.6.2

In my previous post, Oracle BI Applications 7.9.6.2 Now Available, I wrote that Oracle BI Applications version 7.9.6.2 are now available. What I did not include is the download link from Oracle E-Delivery.
Here it is: http://edelivery.oracle.com/EPD/Download/get_form?egroup_aru_number=9149012

So, when you select "Oracle Business Intelligence" from the product dropdown, from the resulting search list, click "Oracle Business Intelligence (10.1.3)...".


This brings you to a page with downloads for 10.1.3.x releases. Oracle Business Intelligence Applications 7.9.6.2 are part of that, because they require Oracle Business Intelligence Enterprise Edition 10.1.3.x version as the underlying platform.

 Happy downloading.

Monday, September 20, 2010

Oracle BI Applications 7.9.6.2 Now Available

The latest release of Oracle BI Applications, version 7.9.6.2 is now available.

Some of the highlights of this release are:

  • Certifications of EBS R12.1.2 and PeopleSoft Enterprise 9.1 sources across all product areas (except CRM).
  • Support for deployment of BI Applications on Oracle Exadata Database Machine via the certification of Oracle.
  • Database 11gR2 as a target database,
  • New capabilities for JD Edwards EnterpriseOne.
  • Full localization to 28 languages.
  • And lots more.
You can read more in the New Features doc (Oracle Business Intelligence Applications documentation).

This software should also be available for download from Oracle E-Delivery.

Friday, September 17, 2010

Visualizations in OBIEE 11g

Wrapped up an Oracle University webcast a few hours back with a colleague, Ken Player, on visualizations in Oracle BI EE 11g.
It covered areas as the new charting engine, interactivity controls, and my favorite - map-based visualizations.

Some screenshots from the session; will provide details in a day or two.

We split up the webcast into three parts. Ken did the introduction and covered visualizations. I covered spatial visualizations and the demo. This slide is where we did the handover.

This slide below calls out, using the same background map, all the six formats you can create with Map Views. The color fill, or choropleth as it is also sometimes referred to, is by far the most popular, and can be put to great use when used in conjunction with the interactive color format slider in OBIEE 11g (more on that in a future post).
The bar and pie graphs are useful if you want to display data across two dimensions. For example, when displaying Revenue data by Country, you can use the bar graph to split that data by product category, or by quarter, or year.
The bubble is useful in its own right since it uses size as the metric variable to call attention. It has an advantage over the color format since the main attribute of the format - the size of the bubble - is based on the metric itself. Unlike in the color fill, where the size of the underlying region can distort perception. A large swath of red over Wyoming versus a small patch of green over New York - are they the same? Not really, because the red appears more prominent because of the size of the state of Wyoming. The area of the color fill in this case is independent of the metric being plotted. Hence the potential for confusion.
The variable shape can be used to great effect if you choose to base the color of the shape on a second measure. Then, both the color and size can be used to convey information. Neat.
And finally, the image format. Need a coffee cup image? A burger icon? A happy smiley? Go crazy with the image formats.


And this has some advanced uses of Map Views.
I will talk about these in much, much more detail in the coming weeks, but here's a short summary:

In the first example ("Multi-Measure, Mixed-Format Maps"), you can plot more than one measure for the same level using different formats. So REVENUE-per-STATE is rendered as a color fill. While UNITS-per-STATE-per-YEAR is rendered as bar graphs.

The second is basically the first map, but with a different background map. You can choose to have a basemap that utilizes a heatmap advanced format to render a completely different, possibly non-BI metric. Like population density. Or income distribution. Or age distribution. Or something else. And then create a map format on top of this basemap.

The third shows that you can use CUSTOM boundaries, and quite seamlessly, in Map Views. Saying "US-Midwest" is not really the same as viewing it on a map.

And finally, maps as the ultimate, lossless, high-density data visualizations. Almost 2000 cells worth of data on that single map. Yes. Data for 40+ states based on one metric. That's some 80 cells of data. Then you have data for 500+ cities, rendered as a variable bubble shaped format, where the size is based on one metric, and color based on a second metric. That's 500 + 500 + 500 cells.

And finally a brief look at the components of a Map View. There are basically two main parts of a map. The first is the basemap, or background map as we call it. And the second is the interactive format.

Friday, September 03, 2010

OBIEE 11g Map Visualizations Webinar on Sep 8

Vlamis Software Solutions, an Oracle Parner, along with NAVTEQ, are hosting a BIWA SIG (that would be the Business Intelligence, Warehousing and Analytics Special Interest Group) web seminar - BIWA SIG TechCast - Sept 8 - Noon Eastern (US) - Information Visualization Using Maps in Oracle Business Intelligence 11g. Use this link to register for the seminar.

OBIEE 11g Certification Matrix - Updated

There have been some changes happening on the Oracle Technology Network. As a result, the link to the Oracle BI EE 11g Certification Matrix that I had posted in an earlier post no longer works.
Use this link instead: System Requirements and Supported Platforms for Oracle Fusion Middleware 11gR1 (XLS format)
Bookmark this page for reference in either case: Oracle Fusion Middleware Supported System Configurations