Intelligent Data Management Framework For Microsoft Dynamics AX

the right time-series DB for your company

Last week, during all the sessions, a nice little update took place for the IDMF, or Intelligent Data Management Framework, for Microsoft Dynamics AX. 

First off, a direct link (PartnerSource or CustomerSource Access Required), to the IDMF download area can be found here.: Intelligent Data Management Framework Download.

Now, let me say this.: Every Customer and Partner, with an AX instance from 3.0, 4.0 and 2009 should be downloading this and looking at it.

If you don't have a good partner, contact me and I can hook you up with a partner that understands the value this brings. 

From the IDMF page.: 

"The Intelligent Data Management Framework for Microsoft Dynamics® AX helps administrators optimize Dynamics AX database layout by providing functionality to manage key database layout techniques, by way of intuitive Archiving and Purging capabilities. 

The framework provides the platform for reduction in database size by purging and archiving of transactions records from sets of relating entities, while maintaining the consistency and integrity of production data. The Intelligent Data Management Framework provides customers and partners the ability to identify and discover related entities based on the Microsoft Dynamics AX metadata and to determine the purging or archiving criteria for tables. 

The Intelligent Data Management Framework also analyzes the Production database to determine usage patterns and assesses the health of the Microsoft Dynamics AX Application. This Framework is compatible with all supported versions of Dynamics AX. The Intelligent Datat Management Framework for Microsoft Dynamics AX is a benefit of staying enrolled in a Business Ready Enhancement plan."

This is meant to be a tool, that resides along side Dynamics AX, to offer a company the ability to archive inactive data, and also remove marked obsolete data. This can happen by Fiscal Year, and done via the options and Dashboard within the client of the IDMF. 

This framwork using Microsoft technologies, that you could create yourself, is being offered to those customers that stay actively enrolled in a Business Ready Enhancement plan, from Microsoft itself.

This framework makes use of SSIS packages, DMV's for Performance, ability to mark and see inactive data and move that data to an archive location, move it back as needed or mark as obsolete for total removal. 

The following is a direct link to a presentation put on by Tao Wang Principal Development Manager Dynamics AX performance, at the AXUG Summit this year: TEC01 - The New Intelligence Data Management (IDM) Tool

Tao does a great job of going over the fact that the IDMF is very much a scalable solution. In that all can be on a single mahince, or as needed parts of it spread and scaled correctly, based on need. 

Up until the release of this tool, Partners and Customers did what this tool already does. Create SSIS packages, use DMV's manaually and understanding what DMV's exists, how to join them and read them. Now, with this tool, both DB health, and size related to indexes, and inactive data can be dealt with, in a nice dashboard fashion. 

I highly recommend downloading this now, and reviewing it. Set it up to hit a test instance of AX, and run through all the options it offers. Archive inactive data, bring it back, look at the performance dashboards, etc. etc. 

That's all for now, but thanks Microsoft for taking and release to the public this great tool!

Till next time!

read more : http://dynamics-ax.blogspot.in/2010/11/intelligent-data-management-framework.html

The Data Management "A-Team"

examples of time series database software

Way back when I was young and impressionable, I loved watching this TV show called "The A-Team". The show started out with what I thought was a very cool quote by an unseen narrator: "In 1972 a crack commando unit was sent to prison by a military court for a crime they didn't commit. These men promptly escaped from a maximum security stockade to the Los Angeles underground. Today, still wanted by the government, they survive as soldiers of fortune. If you have a problem, if no one else can help, and if you can find them, maybe you can hire the A-Team."

So, here I am all these years later, completely living in the dark because while again watching TV (guess I watch too much TV) I see a commercial for a "new" A-Team movie. Like all things in this world, some people will like the new rendition and others will have wished "they" left well enough alone, but you can't make everyone happy.

On the data management side, what we're seeing in industry is very much like the story lines in the original "A-Team" TV shows. Many organizations large and small are suffering because they do not have a data management/governance/quality group in house. For those organizations that do have a group responsible for the health and welfare of data, the teams are typically very small and "A-Team"-ish. [Note: For this posting "A-Team"-ish is being defined as just a handful of folks trying to take on the world and solve problems.] We have seen some organizations without a data management/governance/quality group succeed and not suffer, this is due to having good data practices engrained in their corporate culture throughout the organization. Most other organizations who have not established data management groups will suffer due to their lack of attention on their data. These shops who suffer will on occasion try to hire a contractor (or two, or twelve) type of person(or people) to come in and address data issues when things get bad. These short term engagements typically accomplish the single task at hand but don't come with the long lasting benefits of having an "A-Team" on staff.

What should your data management "A-Team" look like? It depends, but I'd go with the following. 

- A leader/manager to provide direction and prioritization

- A technical lead or data architect, perhaps a DBA or Software Developer who's ready for something new to do, but they must "get data"

- Two or three data analysts: folks who love SQL, are super-detail-oriented and love a challenge

If you're at a large shop, I'd recommend building sets of these groups, as a small "A-Team" can accomplish extraordinary things – kind of like "rinse and repeat" if that makes any sense. As always, executive support is a must, but that's another story in itself which we'll discuss in a different post.

Do you have a data management "A-Team"? If so what does it look like?

Until next time…Rich

visit : http://richmurnane.blogspot.in/2010/05/data-management-team.html

Enterprise Data Management Reality and Perspective

the right time-series DB for your company

Talent and Information are the most Valuable Asset in Enterprise today. 

With exponential growth of business data, Enterprise Data Management needs to put in every mature business’s information agenda, it does not only need to be embraced by the business departments, but by the "enterprise" in its entirety.

1.    Data Management Reality 

For most businesses, there is no difference between Information and data, not to mention the differences between Information Systems and the Technology solution that supports it! Currently organizations are at the different level in managing their enterprise data resources:

1). The old way, there’s no data management strategy, just wrangle with each data store, user, application, and report requirement one at a time. The mentality "I don't need all that other stuff, just give me MY data!" is common. 

2). The ‘hyper’ way, but lack of focus: Organizations get "enlightened", there are many data related titles, and there are a lot of data relevant activities, however, there’re no holistic strategy and clear principle/policy/process in managing data.

3). Return to sanity. Feet back on ground firmly. Realize you can't eat the entire elephant at once, but one bite at a time. You set reasonable goals, build up solid data strategy, create a high-level loose framework, and then start implementing one database, project, reporting requirement, or department at a time.  

2. Information Governance is the Key to Effective EDM

Enterprise Data Management (EDM) implies that there is a strong Information governance which, in turn, supports Data architecture and solution design. There are a couple of options:

1). Businesses enforce EDM across the organization by the proactive support of technology. In other words, mutual agreement and commitment of all C-level members including the will to enforce a common approach in their respective division is a prerequisite for successful Enterprise Data Management. However, in many cases, Information Architecture is the poor cousin in the Enterprise Architecture space with the focus more on implementing technology to try and resolve issues reactively, rather than proactively. Also C level support is something many businesses are struggling to get. 

2). Businesses incrementally build EDM with contributions and buy-in from the different business layers. There is the problem with different business perspectives: What is perfectly appropriate at a senior level will be seen as nebulous at the lower levels. What is perfectly appropriate at the detailed technical level will be seen as deafening noise at senior levels. For this reason some businesses have the different levels of data model, from conceptual downwards through various logical models until got hit the physical world. It could be hard and the slowest process where ROI takes months if not years as there is a certain amount of foundational governance activity and supporting process/tools needed that simply will be difficult to have a hard ROI benefit, but incremental approach lasts the test of time due to business buy in. 

Therefore, the goal of strong information governance is to well balance the long term focus with some quick wins. Broad scope and long term focus are great planning tools and overall targets. But you have to have smaller goals that are achievable in a reasonable time within the current business and IT environment. Nonetheless, to keep up with the competition, businesses cannot afford to complete an enterprise model first, before starting to harvest. They need to follow an incremental approach that ensures a return-on-investment within a reasonable period of time. 

read more : http://futureofcio.blogspot.in/2013/11/enterprise-data-management.html