CIOs, CFOs, and CEOs and Data Cleansing

This is my last full day in Las Vegas for Collaborate 12

I certainly didn’t win at the tables but I did win at the Collaborate 12 conference.

Old friends, new friends, new contacts, hopefully future customers.

MDM is on the rise and it is apparent at the conference.

Thank you to all the Oracle users that had questions this week.

One thing I did observe yesterday was a lot of people had full support from the CIO but…..

The CEO, COO, and the CFO didn’t feel the same passion.

MDM is going to save those people a lot of money and prevent a lot of headaches but they just don’t understand how important it is for them to figure out “what the heck MDM means”.

MDM doesn’t work without great defined business driven data governance coming from those people.

What doesn’t happen is the realization of how important MDM data is to an enterprise.

I saw many industries asking common questions this week.

Oracle Product Data Quality (formerly SilverCreek) was compared to Informatica a lot.  I don’t really know how the Informatica product compares to the Oracle product.  I do know that the Oracle product has had years of building universal product cleansing rules that would work for all product data.  I am assuming the same for Informatica.

Product data cleansing is different than customer data cleansing.   I can go into detail but you need to inquire about the differences yourself.  But at the highest level, you should take a look at the fact that customer relationships and data structures are far more static than product data.  Customer data content is typically the same basic core structure.  Product data can depend completely on the industry, the development processes, the definition of the product, the market channels, regional and global details, etc.  Product data can actually be defined as a result of a good MDM initiative where the customer data is typically cleansed and related in a good MDM initiative.

Experts will agree, disagree, elaborate, or admonish my opinions above.  Either customer or product MDM initiatives are not harder or easier than the other as a general rule.

As a consultant I would advise my client to run any data cleansing and data governance tool through a real test with actual product data.  Whether you pay for this test or whether you get it done during product selection is on you.  But, I would run my data through the tool and see which one gives you the desired results.  The one the does the best job wins.  Ensure that there is no real development effort in this endeavor so that the tool provides a means for business product expert to adjust without code.

Don’t buy a tool that is not easy to setup and use with your data.  It is not the software vendor’s responsibility to extract your data from your legacy system.  Once you have the data extracted into a modern file format like txt, csv, etc, then the tool should be able to pull the data in and analyze.  The tool should suggest changes and accept your feedback.

What is fantastic is if the tool will then deliver the product data cleansed into your PIM Data Hub instance without more code to be written.  Then it can be distributed in a manner that is according to the intense data governance policies that business has instilled into the entire organization.

这是我的最后一天在拉斯维加斯的合作12

我肯定没有赢得在桌子上,但我没有赢得合作12间会议。

老朋友,新朋友,新的联系,希望未来的客户。

MDM是在上升,很明显在这次会议。

谢谢所有的Oracle用户,本周有问题。

有一件事我确实观察到昨天很多人从CIO的全力支持,但…..

(行政总裁)CEO(首席营运官),COO,和(首席财务总监)CFO并没有感到同样的热情。

MDM是要救这些人大量的金钱和避免很多麻烦,但他们只是不明白,他们“究竟发生了什么MDM”是多么的重要。

MDM不工作,没有伟大的定义的业务驱动的数据来自那些人的治理。

什么不会发生的,是实现MDM数据是多么的重要企业。

我看到了许多行业要求的常见问题这个星期。

Oracle产品数据质量(原SilverCreek)的Informatica了很多。我真的不知道该怎么Informatica产品相比,Oracle产品。我知道,有多年的Oracle产品构建通用产品的所有产品数据清洗规则,将工作。我假设相同的Informatica的。

产品数据清洗客户数据清洗是不同的。我可以进入的细节,但你需要查询自己的差异。但在最高的水平,你应该看一看的客户关系和数据结构的事实,更多的静态产品数据。客户数据内容通常是基本相同的核心结构。产品数据完全可以依靠对行业的发展过程,定义产品,市场渠道,区域和全球的细节等。产品数据实际上可以被定义为结果的客户数据通常是一个良好的MDM主动清洗,在一个良好的MDM主动有关。

专家们都同意,不同意,阐述或以上告诫我的意见。无论是客户或产品MDM举措是不是更难或更容易比其他的作为一般规则。

作为一名顾问,我会建议我的客户机上运行的任何数据清洗和数据治理工具通过真实的测试与实际产品数据。无论你支付本次测试,无论你把它做在产品的选择是你的。但是,我跑我的数据,通过该工具,看看哪一个给你所期望的结果。一个是做的最好胜。确保在这方面,有没有真正的开发工作,使刀具企业的产品专家提供了一种手段,没有代码的情况下调整。

不要买工具,这是不容易的设置和使用与您的数据。从旧系统中提取数据,这不是软件供应商的责任。一旦你的数据提取到一个现代的文件格式,如TXT,CSV等,则该工具应该能够拉中的数据和分析。该工具应该提出修改建议,并接受您的意见。

什么是奇妙的是,如果该工具将提供洁净的产品数据没有更多的代码被写入到您的PIM数据平台实例。然后,它可以分配的方式,根据激烈,企业的数据治理策略灌输到整个组织。

Advertisements

About oraclepim

Bob Barnett is an authority on the Oracle E-Business Suite and PIMDH. He has been delivering the Oracle manufacturing and product item master functionality for over 15 years.
This entry was posted in Extending Oracle PIM Data Hub Functionality, Oracle PIM, Oracle PIM Data Hub, Oracle PIM Data Hub Interface, Oracle PIM Implementation Activities, Oracle Product MDM, PIM Data Hub Infrastructure and tagged , , , , , , , , . Bookmark the permalink.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out / Change )

Twitter picture

You are commenting using your Twitter account. Log Out / Change )

Facebook photo

You are commenting using your Facebook account. Log Out / Change )

Google+ photo

You are commenting using your Google+ account. Log Out / Change )

Connecting to %s