Measurement As Blueprint
Getting the front office more involved in data governance begins with creating value for customers
How do you go about making data governance a front-office function – something the business side gets more concerned with?
The primary function of the front office is to build relationships with prospective new customers, and to nurture and grow relationships with existing customers. Therefore, to effectively get the business engaged in data governance, begin by framing every conversation with the front office in the context of creating value for the customer.
If your mandate is data governance, communicate with the front office to help them see that accurate and reliable customer analytics for sales and marketing depend on timely, accurate and complete data.
What are the differences between master data management and enterprise data management? Are these differences semantics or substantive?
The differences are substantive. Master data management is the most challenging component of enterprise data management. It is the blueprint for how data should be organized and classified.
Master data management is the most challenging component of enterprise data management
If the data is organized and classified according to the master data management strategy, then the performance of other key components of enterprise data management, like data governance and data quality, will be greatly improved.
You can't effectively manage something you can't measure. And, conversely, you can't effectively measure something you can't manage.
Are data governance plans producing progress in terms of achieving more effective data management? How is this happening, or not happening?
A partial answer will be found in the self-assessments against ‘compliance' with BCBS239, which the global systemically important banks (G-Sibs) will complete as of December 31, and the Canadian domestic systemically important banks (D-Sibs) will complete one year later.
Firms that are employing industry developed tools, such as the DMMM and/or the DCAM, to assess their compliance against BCBS239 will be well-positioned to objectively answer the self-assessment stocking-taking questionnaire for the regulators.
Secondly, to have more effective data management, your data governance plan needs to always focus on supporting value creation for the customer. If your customer base is growing in size and profitability, credit your data governance and data management capabilities.
Only users who have a paid subscription or are part of a corporate subscription are able to print or copy content.
To access these options, along with all other subscription benefits, please contact info@waterstechnology.com or view our subscription options here: https://subscriptions.waterstechnology.com/subscribe
You are currently unable to print this content. Please contact info@waterstechnology.com to find out more.
You are currently unable to copy this content. Please contact info@waterstechnology.com to find out more.
Copyright Infopro Digital Limited. All rights reserved.
As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (point 2.4), printing is limited to a single copy.
If you would like to purchase additional rights please email info@waterstechnology.com
Copyright Infopro Digital Limited. All rights reserved.
You may share this content using our article tools. As outlined in our terms and conditions, https://www.infopro-digital.com/terms-and-conditions/subscriptions/ (clause 2.4), an Authorised User may only make one copy of the materials for their own personal use. You must also comply with the restrictions in clause 2.5.
If you would like to purchase additional rights please email info@waterstechnology.com
More on Data Management
Semantic density: old wine, or a new vintage?
Giving AI agents enough context to carry out enterprise tasks has become a priority for firms building them, but it’s expensive. It might not have to be.
Firms get AI access to LSEG data via DataBP admin layer
LSEG has expanded its agreement with DataBP to enable customers’ AI-based tools to request and evaluate data from the exchange and maintain more comprehensive usage records.
Rimes builds agents for exception management
The vendor aims to improve its data foundations to allow for greater agent autonomy.
The great migration: Firms work to integrate ISO 20022
Banks and asset managers are working to adopt the new messaging standard, but it’s easier said than done.
PostSig, CJC team up to run data management for London broker
In the first such deployment between the vendors, CJC will act as an outsourced data administrator using PostSig’s technology to manage the firm’s data.
Buy-side firms warn semantic layers not a quick fix for AI integration
Semantic layers promise to teach AI what a firm’s data means. Keeping that meaning current is the part that may get overlooked, tech heads warn.
Mind the stack: the foundation markets run on
Exchange data is an underappreciated component of the AI era, writes Jeff Kimsey.
BlackRock Aladdin prioritizing semantic layer for agentic AI
The asset manager’s tech platform is spending “a lot of time thinking about” semantics before it rolls out AI for a variety of tasks, says Aladdin exec.