Big Data. Big Decisions
InformationWeek
Special Coverage Series

Commentary

Doug Henschen

Doug Henschen

Executive Editor, InformationWeek

Oracle Financial App Targets SAP Shops

Prebuilt analytic application taps SAP to deliver analyses of general ledger, profitability, payables and receivables.

Oracle talks a good game about the appeal of an optimized, all-Oracle stack. But the company also recognizes that we live in a predominantly heterogeneous IT world.

Witness Oracle Financial Analytics for SAP, a new pre-built application aimed at companies using financial apps from one of Oracle's biggest rivals. Introduced on Monday, the app joins a family of prebuilt analytic applications built on the vendor's Oracle Business Intelligence Enterprise Edition (OBIEE) platform.

Oracle Financial Analytics for SAP is based on a nearly identical, preexisting app designed for Oracle E-Business Suite, PeopleSoft and JD Edwards applications. The key difference is in the data integration technology used.

"This is one of the first prebuilt analytic apps we've introduced that uses Oracle Data Integrator [Enterprise Edition], whereas all the other BI applications use Informatica," explained Paul Rodwick, vice president of Product Management, Oracle Business Intelligence.

In all other respects, the SAP version delivers the same financial metrics, key performance indicators (KPIs) and dashboards served up by the original Oracle Financial Analytics app.

Finance managers, comptrollers and analysts in the office of finance get sought-after reports on the general ledger, profitability, payables and receivables. For example, there are prebuilt dashboards and analyses of days sales outstanding, return on equity/assets/capital, payables and bucketed groupings of receivables.

And as in the Oracle-app-focused version, Oracle Financial Analytics for SAP gives line-of-business and division managers prebuilt KPIs and analyses for year-to-year and unit-to-unit performance comparisons.

Oracle could have simply added an SAP data integrator to its existing Financial Analytics App. But it apparently sees value in marketing a separate product aimed at enterprises wedded to SAP as their financials platform.

In fact, Rodwick said Oracle will eventually consolidate the Financial Analytics Apps into a single product that will span Oracle apps, SAP and perhaps other financial applications. That product will let customers choose either Oracle Data Integrator or Informatica's technology for data integration.

"This was an opportunity for us to take the first step and bring SAP customers into the fold," he said.

Indeed, SAP and Oracle aren't just competing on the applications front. They're also trying to get heterogeneous enterprises to choose their respective BI platforms as the companywide standard.

SAP had a head start in that BusinessObjects was the top-selling BI vendor and boasted many integrations with leading enterprise applications even before it was acquired in 2007. Thus, SAP BusinessObjects has a long list of integrations into Oracle products including direct connectivity and ETL-style data integrations for PeopleSoft, JD Edwards, Siebel and Oracle Enterprise apps.

To deliver the kind of analysis provided by Oracle's new prebuilt Financial Analytics app, SAP can point to its own financial analytic apps and to its in-memory technology, as featured in the Business Warehouse Accelerator, SAP BusinessObjects Explorer and the just-release Hana appliance.

Rodwick counters that OBIEE now exploits Essbase, the popular OLAP financial analysis engine (acquired with Hyperion in 2007), as well as techniques such as optimized caching to deliver speedy, what-if analysis.

And when teamed with Oracle Exadata, the vendor's integrated hardware/database appliance, "OBIEE delivers incredible performance, scalability and speed-of-thought responsiveness," Rodwick said.

Long story short, both companies are trying to bolster the appeal of their BI platforms as a standard. Prebuilt apps, appliances and, yes, playing well in heterogeneous environments are all essential ingredients of success -- no matter what anybody says about the vision (our should we say fantasy?) of single-vendor stacks in the enterprise.



Related Reading


More Insights




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.