SAP MDM vs SAP MDG

In last couple of years; I have often come across on my projects where clients ask me what would you recommend SAP MDG or SAP MDM. So I thought I would answer this question today and gather some inputs from the readers

In a nutshell, every MDM implementation is different and what works for one client may not work for other client. 

SAP MDG

Pros

·         SAP MDG is an excellent tool to get started on top of SAP ERP. 

·         In-built governance and validation rules

·         Flexibility of extending and customizing workflow

·         Pre-delivered content - Finance, Material, Supplier, Customer domains

etc...

Cons

·         Not an ERP agnostic tool.

·         Need SAP knowledge to configure the tool

·         Need domain expertise to configure and build additional custom functionality

etc..

SAP MDM

Pros

·         Ability to consolidate master data from multiple sources

·         ERP agnostic tool

·         Inherent data distribution with multiple SAP systems

etc..

Cons

·         Need to build the workflows from scratch

·         Need to build complete set data validations and business rules

·         Need to understand the different modules of SAP solution

etc..

So overall, I have had experience in both the cases where SAP MDG is recommended and where SAP MDM is recommended. What are your thoughts? Have you seen a shift in the mindset based on your MDM implementation experience?

Master Data Management as a Service?

Recently Cloud Computing is on a boom and most of the customers prefer to store their data in the cloud. Google is the biggest example of cloud computing. I personally like clouds; as being in any part of the world i can access my data provided i have an internet connection.

Recently i came across a technology where all the Dashboards and Executive Reports are delivered as a service and the underlying architecture is the cloud.


The application  i am talking about is GoodData. It delivers complete business intelligence platform-as-a-service (BI PaaS) that brings the benefits of cloud computing to the world of business intelligence and data warehousing. Built as a complete integrated platform and offered as a service, GoodData delivers on the fundamental promise of the cloud – on-demand, self-service to deploy and use, and easily adaptable to business requirements.(www.gooddata.com). It also provides an open source API's which any devloper can hijack and customize to their business requirements.

This article makes me think on two thoughts

Thought#1: Business Analytics industry is not matured yet and a recent survey by Deloitte Consulting confirmed it. The results showed only 33% of the US firms are using Dashboards and Executive reports; which is a staggering shock to me. In spite of the several advancements in Business Intelligence and Data Warehousing world, still 67% of firms are not able to implement the BI/DW technology.(http://www.cioupdate.com/news/article.php/3900476/Deloitte---33-of-Firms-Missing-Out-on-Business-Analytics.htm)

And on the flip side  my other thought is:

Thought #2: Would cloud computing help 67% of firms in building the right business technology? Does cloud computing alleviate the challenges that firms face during building their in-house business intelligence platform?

I believe cloud computing has a long way to go. And since my expertise is Master Data Management; i would be really happy to come across a technolgy where i can build Master Hiearchies and build Master Data using the cloud.
 
That would be soo cool; Master Data Management as a Service!!!

As always i am eager to hear my reader's experience and any comments/suggestions are welcome
Talk to you soon!!

Nilesh

Does the frequent upgrades of a product/software affect the end users

Recently i came across a question which was "Does the frequent upgrades of a product/software affect the end users"
http://www.linkedin.com/groupItem?view=&gid=45685&type=member&item=25553748&qid=d6f850cb-3794-4a19-86ec-722190e40d61&goback=.gmp_45685

I would like to share my thoughts on this one.

Based on several years of experience in consulting, i have participated in 4-5 upgrades of various products/software. And in all upgrade engagements i would definitely say that it does take significant amount of resources, time and money. And again it also depends on the reasons why a particular software is been updated.

Is it because
1) A particular bug is fixed for which the client is waiting for, which is majority of upgrade engagements
2) New features have been introduced in the new version and hence the client is updating the software
3) Many a times i have seen the support has been extended to other platforms. For e.g. Initially a tool used to support only Oracle and SQL Server databases, now in the new version it supports MySQL or Netezza

So in every upgrade project, a customer may have different reasons and it is always a process which everyone has to go through. The Best Practice i would like to follow is " Upgrade the software every six months or twelve months depending on the requirements. 12 months if the requirements are not severe or if we can a get a feature which would be beneficial for IT; it should be six months"

To summarize,
The pros i have seen are end users get new features in a product, extended support to different breed of platforms and cons i see as time, money and resources and majorly the confidence of the end users and most of the time its difficult to buy in the end users.

And to answer the question it does affect the end users, as they have to be made aware of the new features in the tool and again a training process has to be followed so that users get familiar with the new version. In my experience a minor version does not changes the product in and out compared to major version. So it is a case by case implementation and requirements, scope can be different in every implementation.

What have been your experiences? Do you have any best practices or recommendations which should be followed during upgrade engagements?

Nilesh Makhija

Toad 9.0 with Oracle 11g

Here are my two cents on connectivity issues between Toad and Oracle 11g...

Everyone knows about Toad and is the most widely used tool for connecting to Oracle databases. We use Toad all the time to connect to Oracle 10g databases. But recently we upgraded one of our environments to Oracle 11g and Toad stopped working. (Dont we have such issues all the time?)

Basically this is the issue:
I tried connecting to Oracle 11g using Toad 9.1 and it popped an error saying invalid username/password. So i used SQL Plus, Native connection of Oracle and tried connecting it to 11g environment and expected i will get the same error, but guess what SQL Plus got connected.

So Toad was unable to connect and SQL Plus got connected. Then i installed SQL Developer and again surprisingly SQL Developer also got connected using the same tnsnames.ora file. So there was something going on with Toad; which i needed to find out.

So basically this was the issue

In Oracle 11g, we have a variable called SEC_CASE_SENSITIVE_LOGON which says whether case sensitivity should be enabled for password or not during the logon

And keep in mind this was introduced only in Oracle 11g and none of the previous versions of Oracle had this parameter for the "password case sensitivity".

Now if sec_case_sensitive_logon = true, Password case sensitivity matters
and if sec_case_sensitive_logon = false, Password case sensitivity does not matters.

Now issue on the Toad side, it converts all the passwords to Uppercase(which is a bug in Toad 9.0). So the workaround is while connecting using Toad, enter username and keep the password field blank and Toad will prompt a dialog box asking for password, and then enter the password...and there you go..You successfully connected to Oracle 11g.

Or the other solution is change the sec_case_sensitive_logon and set it to False, using the following query
alter system set sec_case_sensitive_logon=false


Just sharing my knowledge....as i learn

Nilesh Makhija

Multiple Data Feeds in Kalido 8.5

As we have seen in most of the Data Warehousing projects, we try to run the reference data loads in parallel and increase the number of threads so that we can maximize the resources allocated to the Database Server. With Kalido also we can run the parallel loads but we need to keep a small thing in mind that we cannot run the parallel loads on the same object in Kalido Warehouse. Meaning; if we have a GL Account CBE and this CBE is being seeded from two source Systems SRC1 and SRC 2, we cannot run the loads from the 2 source systems at the same time. For sure these can run back to back but not in parallel with each other. And the reason for this is Kalido locks the object and only one load can update that object(in our example GL Account CBE). So if we try running another load while one load is in progress,the second load will error out. Consider yourself lucky, as Kalido generates a log file which can be decrypted by a human being with an error message "Another Load is in Progress".

So if we have feeds from various source systems loading data into the CBE, they should be executed sequentially. A dependency has to be build saying that when one load is complete, trigger the next load on the same object. For sure we can execute the different feeds for different objects and in that way parallelism can be achieved but not on the same object. We could increase the number of threads while loading the data, but not greater than 4(loads start degrading after 4)

So the thought for the day is "Never Ever run multiple data feeds on the same object in Kalido at the same time"


As usual Enjoy working with this great tool....

Nilesh Makhija

Oracle V/s Kalido

Hello,

There is an interesting link i came across which talks about implementing warehouse using Oracle Suite V/s implementing warehouse using Kalido tool and the back end database is still Oracle.

Kalido tool will just function as a tool and will automate much of the manual stuff and would also factor in some of the ETL functionality

Here is the link and let me know your feedback

Oracle V/s Kalido

Cube V/s Data Marts

Cubes and Data marts

I am sure all you guys who have worked in warehousing practice, have at least heard these words and many of them actually have implemented these concepts...Cube and a Data mart

Recently i was having discussion with my peers in BI/warehousing pratice, on what are the differences between Cubes and Data Marts...and to my surprise..the discussion as not so productive as we digressed to diferent terms like OLAP and ROLAP...as no one was clear which way to go for a particular scenario.

So basically i am asking is two questions
1) What are the differences between a Cube and Data mart?

I've also had folks tell me that a data mart is more than just a collection of cubes. I've also had people tell me that data mart is a reporting cube, nothing more...

So what are the distinctions you understand

2) In what scenario would you choose cube over Data Mart and vice versa?

Waiting for your inputs...

--Nilesh