1月 062017

Much of my recent work has been along the theme of modernization. Analytics is not new for many of our customers, but standing still in this market is akin to falling behind. In order to continue to innovative and remain competitive, organizations need to be prepared to embrace new technologies […]

The seven traits of a modern analytical platform was published on SAS Voices.

7月 072014

200426063-001As a Data Management expert, I am increasingly being called upon to talk to risk and compliance teams about their specific and unique data management challenges. It’s no secret that high quality data has always been critical to effective risk management and SAS’ market leading Data Management capabilities have long been an integrated component of our comprehensive Risk Management product portfolio. Having said that, the amount of interest, project funding and inquiries around data management for risk have reached new heights in the last twelve months and are driving a lot of our conversation with customers.

It seems that not only are organisations getting serious about data management, governments and regulators are also getting into the act in terms of enforcing good data management practices in order to promote stability of the global financial system and to avoid future crisis.

As a customer of these financial institutions, I am happy knowing that these regulations will make these organisations more robust and stronger in the event of future crisis by instilling strong governance and best practices around how data is used and managed.

On the other hand, as a technology and solution provider to these financial institutions, I can sympathise with their pain and trepidation as they prepare and modernise their infrastructure in order to support their day to day operations and at the same time be compliant to these new regulations.

Globally, regulatory frameworks such as BCBS 239 is putting the focus and attention squarely on how quality data needs to be managed and used in support of key risk aggregation and reporting.

Locally in Australia, APRA's CPG-235 in which the regulator has provided principles based guidance has outlined the types of roles, internal processes and data architectures needed in order to have a robust data risk management environment and to manage data risk effectively.

Now I must say as a long time data management professional, this latest development is extremely exciting to me and long overdue. Speaking to some of our customers in the risk and compliance departments, the same enthusiasm is definitely not shared by those charged with implementing these new processes and capabilities.

Whilst the overall level of effort involved in terms of process, people and technology cannot be underestimated in these compliance related projects, there are things that organisations can do to accelerate their effort in order to get ahead of the regulators. One piece of good news is that a large portion of the compliance related data management requirements map well with traditional data governance capabilities. Most traditional data governance projects have focused around the following key deliverables:

•      Common business definitions1397487016440

•      Monitoring of key data quality dimensions

•      Data lineage reporting and auditing

These are also the very items that the regulators are asking organisations to deliver today. SAS’ mature and proven data governance capabilities have been helping organisation with data governance projects and initiatives over the years and are now helping financial institutions tackle risk and compliance related data management requirements quickly and cost effectively.

Incidentally, our strong data governance capabilities along with our market leading data quality capabilities were cited as the main reasons SAS was selected as a category leader in Chartis Research’s first Data Management and Business Intelligence for Risk report

The combination of our risk expertise and proven data management capabilities means we are in a prime position to help our customers with these emerging data management challenges. Check out the following white papers to get a better understanding of how SAS can help you on this journey.

•      BCBS 239: Meeting Regulatory Obligations While Optimizing Cost Reductions

•      Risk and Compliance in Banking: Data Management Best Practices

•      Best Practices in Enterprise Data Governance


tags: compliance, governance, risk
12月 192013
In my previous post, I talked about planning your MDM initiative and the importance of data quality and data governance to the effort. Today, we're going to drill in a bit into Master Data Management Foundations, a SAS offering unique in the marketplace that serves as a bridge between data [...]
10月 082011
With details of the UBS incident still coming in, the topic of rogue trading was in the air as the Committee of Chief Risk Officers (CCRO) held its second annual risk summit in Houston on Sept. 21-23. It’s natural for a gathering of senior risk practitioners to engage in some [...]
9月 192011

imageFor the many years that I have been involved in the area of enterprise information management, I have seen organisations struggle with the issue of data quality over and over again. I have seen the IT departments struggling with the delivery of so called “Data Quality” projects, and I have also seen businesses struggling and complaining about not being able to get access to “Quality Data”.

Seeing that Data Quality technologies have matured over the years and SI’s have become reasonably good at delivering data quality projects, what exactly is the problem?

Among many different factors, I believe the two main reasons that organisations are still struggling with trusted data today are:

“Data Quality technology is not the only component needed to build and deliver trusted data at an enterprise level.

In order to gain trusted data, Business needs to be more involved in the Process along with IT”

That’s where Data Governance comes to the rescue. What data governance provides organisations is a more holistic view and framework in how they manage, control and leverage their data assets so their value can be maximised. It is the missing layer that links the necessary underlying data quality technology to the ultimate goal of trusted data. Specifically the layer that data governance inserts includes the people and process aspects that have been missing in the IT driven, pure data quality projects of the past.

What organisations have come to realise is that Trusted data depends on having a robust data governance framework and that a robust data governance framework will need a flexible, proven set of data quality tools to enforce the processes and rules. You can not have one without the other as they are intrinsically linked to each other.

There is no question that the detail of such undertakings and initiatives can be complex and extensive. If we just focused on the people aspects, things that organisations needs to come to grip now with include:

  • The right level of executive/board level support
  • The right organisational structure to support the initiatives
  • The identification and assignments of data stewards

As a starting point for anyone in charge of delivering any data governance initiatives, the people element is perhaps the most critical and important one to even get the projects off ground. Here are a couple of whitepapers that goes into more detail to help you get started.

I believe that the shift from data quality to data governance is a positive one. It has elevated the discussion to the executive level and is allowing organisations to think about important elements that were missing in previous discussions or projects.

With the right foundational components and the involvement of business through the appropriate process, I believe organisations will be one step closer to delivering trusted data throughout the enterprise.

tags: data quliaty, governance