How effective is your data governance program

In this, the conclusion of my blog series on “Measuring data governance programs,” I’ll be exploring the need to measure data governance process performance and techniques you can use to ensure that those processes are operating optimally. Read more

Key capabilities for data governance

As you read recently, Kalido announced a new version of Kalido Data Governance Director that added new capabilities that further automate data governance programs, improving efficiency of business processes through delivery of trusted information. Read more

Noetix for Oracle E-Business Suite Reporting — The Choice of Global Industry Leaders

We caught up with some Noetix customers at a recent industry tradeshow and asked them a few questions about their Oracle E-Business Suite environments, how they would describe Noetix in a few words, and any advice they might have for someone evaluating BI tools. Two of these customers have been relying upon Noetix for reporting for more than six years.

Featured Noetix customers include: Robert Loreto, Senior Director IT Finance Systems, Qualcomm; John Cannava, Executive Director of Financial Systems and Billing, TeleTech; and Lance Miller, Director of Corporate Applications, Iberdrola Renewables.

Watch Video (2:57)

Introducing Noetix Analytics for Oracle Financial Statement Generator

Noetix Analytics 5.0 was released last May, and more recently we’ve been diligently working on Noetix Analytics 5.1, which shipped in February. Noetix Analytics 5.1 has a big emphasis on new content including a powerful new feature called the Financial Statement Generator (FSG) data mart.

During months of development for this solution, we engaged the help of several partners and worked with them to identify challenges they experienced with their existing Oracle FSG reporting. We found they had limited drill-down capability with hundreds of existing FSG reports. They recounted that it was difficult to maintain the Application Desktop Integrator (ADI) and experienced loss of functionality when upgrading to R12. In addition, their FSG reporting was not integrated with their enterprise BI platform and data warehouse.

In response to these and other issues, we are introducing Noetix Analytics for Oracle FSG, a packaged data mart, including ETL routines, and a set of report templates that reproduce your existing Oracle FSG reports in your BI platform of choice, including Oracle Business Intelligence Enterprise Edition, Cognos, or Business Objects. In this way, Noetix preserves and extends the value of our customers’ investments in Oracle FSG reports.

Users will also benefit from dramatically superior drill-down capabilities provided by Noetix Analytics. Not only can they now see the FSG reports in their BI platform, they also have much better ability to interact with that report, and can drill to account balances, journal details, and ultimately all the way down to the sub-ledgers.

We’re very excited about this new capability and believe there will be a lot of demand for the solution. More details are available via this On Demand Web Seminar: Discover What’s New in Noetix Analytics.

Forget Multi-Domain; Integrated Master Data Is the Prize

Over just a couple of short years, every MDM product in the universe has become multi-domain, the enterprise software edition of Extreme Makeover. Let’s not even get into data governance…

Data Integration, Profitable Business Decisions & the Lawn Man

My lawn man fired me last week.  Actually, he fired my wife Candy and I was just the collateral damage. Read more

Developing Analytic Applications is a Collaborative Process – Research Study of 250 IT Professionals

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

In many organizations, the IT department has the responsibility and the expertise to explore, develop, and install most major applications, as well as identify technology that can support an organization’s mission. While senior management must sign off on any significant new project, the IT group takes on the burden of such initiatives.

However, the process of identifying, developing, and implementing analytic applications is a much more collaborative process according to a research study conducted by the Lattanze Center, a nationally recognized center of excellence on issues related to business excellence and IT at Loyola University Maryland. To an overwhelming degree, IT professionals and end users work together to select and develop analytic applications.

In a survey of more than 250 IT professionals who indicated that analytic applications were used in their organizations:

  • 71% reported that selecting analytic applications was a joint decision made by IT and end users
  • 10% said that IT alone chose analytic applications
  • 5% indicated that end users alone selected analytic applications

The same pattern of collaboration held true for developing analytic applications. Among the respondents to the survey:

  • 56% said that IT professionals and end users work together to develop analytic applications
  • 24% reported that IT professionals alone created analytic applications
  • 9% indicated that consultants were responsible for developing analytic applications
  • 4% said that end users were entirely responsible for developing analytic applications

This data suggests that in many organizations end users do not have sufficient technical skill to build applications without assistance, nor are they empowered to select analytic applications entirely on their own.

On the other hand, end users do routinely collaborate on both the selection and development of analytic applications. The reason is not hard to determine. Analysis is a quintessential “ground up” activity. End users know what data they need and how they want to analyze it, while IT can identify and suggest new tools that could be potentially useful.

To a degree, the level of cooperation between end users and IT during the development process declines. While end users simply may not have the technical skills needed to assist in development, a high degree of interaction is needed to ensure the analytic tools selected, developed, and implemented can generate data and lead to the answers the end users want.

Stay tuned for part three of this series in the July/August 2011 issue of the Noetix Newsletter! We will take a look at the amount of time it takes for an organization to go from the decision to create a new analytic application, to having the application operational, including the biggest challenges found along the way.

Building a Culture of Analysis

By Elliot King, Ph.D.
Professor of Communication, Loyola University Maryland & Founder of the Digital Media Laboratory

The idea that we live in an age of information abundance has been a cliché for the last generation. With huge amounts of data being regularly generated, developing the ability to understand and apply that data for decision support, trend analysis, and predictive analytics has proven difficult.

The problem isn’t the lack of data or tools for analysis. The real challenge is three-fold:

  1. Companies must decide what they “want to know” that they “don’t know” already and identify which data and analytic tools will generate that information.
  2. They must have enough confidence in the information produced to incorporate it into decision-making and organizational processes.
  3. They must continually assess and build on the first two. Are they conducting the right kinds of analyses to improve business performance in measurable ways? Are as many people as possible making fact-based decisions that are leading to better outcomes?

Those three elements are the foundation of what could be called a culture of analysis — a culture premised on the idea that understanding the underlying patterns in past and present data will lead to improvements in the future.

Companies can take several steps to create a culture of analysis:

  • Assess how deeply the idea and practice of analysis has penetrated the organization to date. What analytic tools does the company have? How effectively are they used and by whom? Who utilizes the output of the analysis and how does it help them do their jobs?
  • Ask difficult questions. What information would be helpful to know that is not currently available? Does the company have the resources to develop that information from the data available? Does the company need to cast the information-gathering net wider to include unstructured data from outside databases or from third-party sources?
  • Create a strategy for broadening analytic capabilities. Can elements of the analytic process be automated to accelerate time to insight? Can the way data is visualized and promoted be improved? Can the use of analysis throughout the organization be broadened?
  • Set expectations. What kind of data and analysis must be generated before a decision will be made? How long will decision-makers wait to access that information? If people know that they are expected to justify their actions with data, they will.

Analysis is an iterative exercise. As more data is produced, companies are under great pressure to make better use of it. Developing a culture of analysis is critical in that effort.

What is the average length of time between a Noetix implementation and the delivery of reports to end users?

QUESTION:  What is the average length of time between a Noetix implementation and the delivery of reports to end users?

ANSWER:  Every BI project is different, but there are some general facts that are true for every Noetix implementation. For real-time operational reporting (using NoetixViews), the initial implementation is deceptively easy, so the time to deliver the first reports is unbelievably short. Packaged analytics with a data warehouse (using Noetix Analytics) can be more complicated and generally takes a bit longer. Still, using the packaged data warehouse solution from Noetix yields results faster than any other data warehouse approach.

Let’s look more closely at each option.

To implement real-time operational reporting, the patented Noetix MetaBuilder process automates a great deal of the manual (and usually tedious) work. Noetix MetaBuilder detects details about your configuration of Oracle E-Business Suite and uses that information to generate custom database views. Noetix Generator integrates details of those database views into your BI platform: Oracle BI EE, Discoverer, Cognos, BusinessObjects, or Noetix Platform. The processes to create the views and integrate that information into the BI platforms completes within just a few hours. Literally, users can run reports within the first day or two of implementation.

Implementing strategic reporting using a data warehouse requires more effort because there are more moving parts to the implementation. New dimensions, metrics, and hierarchies usually need to be created. ETL scripts may need to be modified. External data sources often must be integrated. Noetix Analytics includes tools to simplify all of those tasks, but they still need to be done. Projects to implement Noetix Analytics are typically at least a few months long. However, Noetix takes an iterative implementation approach (implementing individual subject areas one by one) so that reporting on the first modules can begin within thirty days.

Of course, with both kinds of projects there are always ongoing customizations, new reports and dashboards to build, performance tweaks to make, and training to complete (both for users and administrators). For most customers, the initial implementation of Noetix’s operational reporting solution takes about a month – we recommend four to six weeks. After that, users will always want more reports, access to additional data, performance optimization, and new functionality. For Noetix Analytics projects, we recommend two to four months for an initial implementation. By industry standards, that’s exceptionally fast, much quicker than building a data warehouse in-house or implementing a solution from another vendor that won’t meet the needs of your organization.

Submit a question to Noetix and check back for the answer in an upcoming blog post!