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Data service organisation - to enable business requirements

Central for de-central data teams: start acting as a (temporary) data owner to service business requirements.

Set up data service desks to be flexible for business requirements.


Data is often seen as the raw material to produce new products, frequently with analytics and AI as the innovative machinery enabling the end-result. Recent years have proven that the value of data more often serves as an enabler of multiple business results, leading to efficiency savings, profits, and the ability to maintain existing markets while expanding into new ones

Data as fundamental oil

Whether it is automated payments and invoicing, online customer interactions, or digital manufacturing, data is the underlying oil that can make your business operations run smoothly.

Or does it? Why is it that, despite the abundance of data, businesses often run sub-optimally, sometimes even relying on manual activities, in this digital age?

“So, if data is the new oil,

why isn’t everything running smoothly?”

All companies generate, receive, and process data to some extent. Data is abundant these days. So, if data is the new oil, why isn’t everything running smoothly?

Here is why: the data itself is complex, and the usage of data is complex. Many companies have tried to resolve this combined complexity through centralized standardization. Many projects aimed at establishing a single data model have become famous, often leading to disappointments. Alternatively, data solutions seek refuge in technology, often resulting in an increase in applications, which can add to the complexities instead of alleviating them. Above all, centralized standardization requires control, which does not adequately serve the business.

Move from control to empower

The very essence of any business is flexibility, the ability to innovate and develop new products and markets. The business needs to be facilitated by data. So, move from controlling towards empowering.

Empowering means understanding that there is no one-size-fits-all when it comes to data, as in the above-mentioned complexities. Data is very similar to machinery. Just compare the oil for ball bearings to petrol. They share the same raw material but differ in volume, characteristics, substance, and processing for different purposes.

How do we see the solution?

With the extensive rise in data volume, complexity, and velocity, a central data team supported by data stewards and architects is no longer sufficient. It requires more decentralized teams that can facilitate specific business needs while adhering to central requirements. Use the motto: control only where needed – for example, using one standard product or client ID across systems, and facilitate where possible, such as adding an additional product ID to support a regional process. Of course, this requires more effort. It is evident that any additional data requires more maintenance. However, the benefits for the business are immediate and significant. There is no need for the business to change processes, systems, or reporting. Immediate possibilities emerge to make more local variations of products and insights, facilitating specific market requirements. This approach maintains the possibility of working with central initiatives and the option to upgrade or downscale data where possible without affecting central requirements.

“The answer is easy, the deployment is more complex “

How do you facilitate this? The answer is easy; the deployment is much more complex. Have dedicated data teams in place with a close relationship to the business. That data team should consist of senior, well-trained data management experts, data analysts, and data engineers to facilitate and guide the local solutions, including the link to central platforms. The team should be able to answer business questions through a so-called service desk. Such a service desk requires a thorough understanding of the business processes and systems and the translation of data requirements into existing (or missing) data within systems. Preferably, the service desk should have the capability to identify, flag, and resolve regulatory questions on privacy, financial legislation, and health legislation. Make sure that the service desk is enabled by a ticketing workflow, including a dashboard displaying their effort and impact. Finally, that data team should be able to guide the business stakeholders in the best approaches and solutions. Don’t expect business stakeholders to deliver data requirements; they will have business requirements. If you didn’t know better, this team almost acts like a data owner.


Of course, some data needs to be strictly governed and controlled. There are overarching business requirements (e.g., insights in sales volumes) that require consistency and quality of trusted data. Identify these key data elements and manage them with a strict and tight regime. These key data elements can. for example, be linked to key reporting, identified as being used for most processes, or be the primary key within multiple systems. Current data volumes can make this identification a tough job. A good start can be using the Dublin Core standard to identify the right regime. The standard uses the following guidance:
– which data is related to which process, system, product and report?
– where is data being used?
– why is the data needed (purpose)?
– Who uses the data?
– How is data labelled and referenced?
– What is the relevance of the data (e.g., static or dynamic)?
– How is data related to other data?

New way

Teams acting as (temporary) data owners is a new, almost revolutionary way of looking at data. The traditional view, based on data standards (e.g., DAMA, DCAM, ISO), all revolves around governance and ownership. That view is based on having data ownership within the business. If you step away from that theoretical view and fall back on lessons learned, then don’t expect business stakeholders to take up sufficient data ownership. For decades, they have perceived data as a by-product.

Most business stakeholders will stay away from data ownership simply because it is unknown territory for them. It is up to the data team to translate do’s and don’ts regarding data and take up data ownership for the business. In theory, this might even support the embracing of data ownership by business stakeholders through the principle of show and tell.

So, a team of experts is required. Such a team goes beyond the effort of some companies to “simply” assign a data steward who reports on the content of specific fields within systems. Companies should build dedicated teams across the organization, which will often need to invent the wheel themselves. The way of working will differ per objective. For project goals, make sure you can act fast, agile, and dedicated. For sustainable solutions, ensure that you stay completely aligned with company standards (and enhance a few where needed) to avoid the “not invented here syndrome.” For any purpose, make sure you take the time to understand and align data, data requirements, and business requirements. And actually build solutions – not just on paper, but within apps, databases, data pipelines, and systems.

All of this will require a solid, robust, and senior data leadership team which can manage, sustain, guide and facilitate data responsibilities. Invest in that team.

For examples on data standards, visit: DAMA, DCAM or ISO

Using Data Mesh to Organise Data Management

We recently visited Sander Kerstens to talk about his Data Mesh implementation at Vanderlande. Data Mesh is a new approach to organising enterprise data. It aims to make managing and using data easier for everyone involved. 

Traditionally speaking, data management is organised through a centralised team that is responsible for all enterprise data. Data Mesh decentralises this, by distributing this responsibility across smaller teams (called domains) within the enterprise. Instead of having central policy and standards that are applied across enterprise teams, teams define their own policies and standards instead. 

In Data Mesh, each domain is responsible for the data they generate, the domain decides how their data is managed, processed and shared with other domains. All domains work together in a networked architecture. In turn, allowing for greater collaboration and ability.

A core principle behind the Data Mesh philosophy is one that we often write about: treating data as a product. As a product, there should be clear documentation and standards that describe that data is used and maintained. Much like in traditional data management, Data Mesh stresses the importance of good metadata.

By empowering smaller teams to take ownership of their data and work more closely with other domains, Data Mesh can help organizations to scale and innovate more quickly and efficiently. It bases data management hygiene factors on its principles, rather than having a central data governance team dictate how teams should act. 

This introduces a different way of thinking, which may be more suited to modern enterprises. This depends on the culture of the enterprise, though. One approach is not necessarily better than the other, both have their own strengths and weaknesses which are outlined below. 

Traditional Data Management

ProsCons
Greater control and consistency Potentially slow and inflexible 
Close alignment with business strategyMay not need team/domain specific requirements
Close alignment with regulatory requirementsMay not need team/domain specific requirements

Data Mesh

ProsCons
Agile and responsive to changing business needsCan help foster innovation and collaboration between teams
May present challenges around data quality and consistencyComplex to implement in terms of culture and technical debt

Material Science with Materials Zone

Ori Yudilevich (Chief Technology Officer at Materials Zone) on: the history of Materials Zone, the company and its product. Ori explains how Materials Zone’s Materials Informatics platform applies material science techniques to save costs. He also explains what challenges with regards to data they usually come across.

D8A Directors
D8A Directors
Material Science with Materials Zone
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Trends and Developments in Data Analytics Consulting

Ryan Price (Executive Data & Artificial Intelligence at Avanade) on: trends and developments within data analytics consulting. Ryan talks about how Avenade approached data and AI on a global scales and discusses his views regarding important topics around data and AI.

D8A Directors
D8A Directors
Trends and Developments in Data Analytics Consulting
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Tailor made D8A Academy trainings

Members and partners of D8A Directors can bring their years of experience as hands-on training to your organisation.

Are you looking for inspiration, guidance and practical how-to’s in building your data driven organisation?

Some inspiration on topics:

  • Guiding change through enterprise data architecture practice
  • How metadata management enables you to find, understand, govern, trust and share your data
  • Growing a federated data governance in your organisation made practical
  • Where and how to start with data quality management with immediate cost reduction in business operations
  • How to transition the perspectives of data security, privacy & compliance from ‘cost center’ to ‘profit center’ when done right
  • How to organise data products in data mesh
  • How to realize data observability embedded into your data pipelines with databricks and deltalake
  • and other

Don’t hesitate to get in touch with your case for a trailor made training!

Data-driven asset management

Jan Leenaars(Product Owner at Rijkswaterstaat) on: data-driven asset management, how data can be leveraged to manage assets, common pitfalls and lessons learned. Jan talks about how users & developers can work effectively together to create reliable insights on time. Listen to hear how Rijkswaterstaat has faced data-driven asset management challenges and how they overcome these challenges.

Date with D8A
Date with D8A
Data-driven asset management
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How to Become a Successful Data Professional

Remi Verhoeven (Senior Manager at KPMG) on: the character traits, technical skills and soft skills required in order to become a successful data profession. Listen to hear about the ways data professionals can improve their skills to increase their chances in the recruitment process.

Date with D8A
Date with D8A
How to Become a Successful Data Professional
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How to boost data availability? Synthetic data is the answer!

Wim Kees Janssen (Co-founder of Syntho) on: data synthetisation, what it is, what it can be used for and how it adds value to organisations. Wim Kees talks about how synthetic data helps speed up Development, Test, Acceptance and Production (DTAP) cycles by making privacy a non-issue. Listen to hear how Syntho provides the technical solution to root out the need for production data and mitigate possible privacy risks.

Date with D8A
Date with D8A
How to boost data availability? Synthetic data is the answer!
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Data strategy for small and medium-sized enterprises

Geneviève Meerburg (Director SME Services at van Spaendonck) on: implementing a data strategy within her organisation. Geneviève shares how the importance and value of data organically grew, leading to a concrete need for a data strategy. Listen to hear how van Spaendonck approached truly living through the principles set out in the data strategy and how it helped create new services for their clients. 

Date with D8A
Date with D8A
Data strategy for small and medium-sized enterprises
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Trusted data awareness

Arjan Pepping (Corporate Data Manager at MN) on: creating awareness around trusted data and the role of data in control for a pension provider. Listen for the golden tip on implementing data awareness.

Date with D8A
Date with D8A
Trusted data awareness
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Good design teams embrace data quality

Marinka Voorhout (Director at Philips) on: data quality in design is becoming a pre requisite for innovations on data. Listen to practical approach tips and ideas to take data quality into account in user interfaces.

Date with D8A
Date with D8A
Good design teams embrace data quality
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Trailer: Date with D8A

In this trailer of the Date with D8A podcast series, Simone from D8A explains the idea behind the D8A initiative and the what, why and how of the Date with D8A podcast.

Date with D8A
Date with D8A
Trailer: Date with D8A
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