Data Flux
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The document discusses the journey organizations take to establish trusted data through effective data management. It outlines key barriers such as a disconnect between business and IT needs as well as a lack of data ownership and governance. The document promotes establishing repeatable data processes through a single data management solution that provides data quality, integration and master data management capabilities. This helps improve business user productivity, reduce costs and risks, and support data-driven decisions.
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Data Flux
- 1. “ The Journey to Trusted Data” Saul Cunningham DataFlux ANZ General Manager 10 March 2011
- 2. Welcome Saul Cunningham Managing Director, DataFlux ANZ
- 3. Where are you on your data journey?
- 4. Planning is the Key
- 5. The Evolution of Data Awareness
- 6. The Current State of Data Management The top four potential barriers to coordinating data management initiatives
- 10. The Data Governance Maturity Model Sales Force Automation Database Marketing IT-driven projects Duplicate, inconsistent data Inability to adapt to business changes Data Warehouse ERP CRM Line of business influences IT projects Little cross-functional collaboration High cost to maintain multiple applications IT and business groups collaborate Enterprise view of certain domains Data is a corporate asset Customer MDM Product MDM Materials MDM Employee MDM Asset MDM Business requirements drive IT projects Repeatable, automated business processes Personalized customer relationships and optimized operations MDM Business Process Automation
- 14. DataFlux – one solution with broad application across your business “ It’s like having a “Swiss Army knife” suite of tools to characterise, clean, integrate and monitor the quality of BP’s data.” Ken Dunn (BP Data Architecture Manager)
- 19. Questions?
- 21. Conceptual View of Master Data Management SFA ERP Data Warehouse Call Center Apex Equipment Pty Ltd | Newcastle Apex | Newcastle, New South Wales Apex Construction | Newcastle NSW Apex Equip & Const | Newcastle NSW Apex Equipment & Construction, Pty Ltd | Newcastle NSW 2300 Batch | Real-Time Batch | Real-Time Batch | Real-Time Batch | Real-Time Data Integration Data Quality Data Model Business Services Stewardship Console Business User Interface Data Governance Identity Management Reporting Data Profiling Metadata Discovery Business Rule Definition Entity Definition
Editor's Notes
- My name is SC I run Dataflux ANZ We are a wholly owned subsiduarary of SAS We specialise in Data Management and are the leaders in Data Quality according to Gartner We provide DI and MDM solutions as well as DQ Our software sits inside many SAS products like EDI server and DI server etc Possibly you own it without realising it. Possibly you use it without knowing its full potential. Drop by our stand and get to know us. Today I only have 25 mins before I get kicked off I won’t have time to go down into the weeds What we will do is cover What Why and How of MDM.
- Speaking of Data Stewards and Data Governance its important to understand that MDM is an evolutionary process You don’t just go there in a day Organisations range from being undisciplined through to governed Indeed right now in our experience over 80% of organisations would be in the undisciplined or reactive phases. In these phases they are really IT lead with departmentally funded projects adding to the siloed nature of their data They tend to be driven by external events like compliance reporting or the implementation of a new major CRM system There exists a chasm between the reactive and proactive phases that has nothing to do with technology This chasm can never be crossed until multiple business units together with IT collaborate around business process that spam the enterprise. These business processes will need data that is accurate and current Often the business process in question might be customer focussed – say order-to-cash and so this drives the adoption of domain specific customer MDM Other times the process might be procure-to-pay and so drive supplier and materials MDD As time goes by and this focus moves beyond individual business processes to a complete enterprise view multi-domain MDM and business process automation It is here that we see the biggest paybacks with lowered risk in things like customer churn and compliance Key element though is that this is all about getting buy in from the different LOB’s and IT to work towards our common goal of our MDM charter
- So lets have a look at how it works at a conceptual level Here we see a customer MDM example – Apex In the various systems – Call Centre, Sales Force Automation, Enterprise Resource Planning etc various versions of Apex exist They may have different names, different addresses, ABN numbers, contact information etc The central MDM hub holds what is often called the “Golden record”. It has a strict definition. Now at this point we could talk about different models of MDM. All I am going to say is The hub can actually store this information itself Or the hub can hold references to which system holds the “golden name”, the “golden address” etc Various combinations of these approaches exist and various synchronisation schemes exist For the purpose of this presentation it is enough for us to think about this at a conceptual level and understand one key thing. The apps are still responsible for the owning and managing the transaction data i.e the Call Centre system will still be responsible for recording the customer interactions The SFA app be responsible sales The ERP for interacting with suppliers etc However they will no longer own the Master Data Why? What is the reason for this shocking truth? Well if they each do that still we will still have multiple version of the truth At its heart MDM is about decoupling the applications from the common, business wide master data and managing it as an application independent asset This can be heard to hear for some but it is the only way to fix the problem of “too many watches” As you can imagine the biggest hurdle is not technology but political. In fact the technology is straight forward The tools we need all exist and are shown on the slide Data profiling and discovery – to help us find out what exists in the source systems and what state of health its in Metadata tools – to help us define definitions Data Integration tools to interact with the source systems and merge information together Data Quality tools to cleans, deduplicate the data down to a single record The ability to render the data as a business service for consumption by the source systems and my users