What makes a data-driven enterprise? Amplifi examines the relationship between culture and technology in a modern data ecosystem.


With organizations collating more data than ever before (data volumes have doubled in just three years), businesses are fast outgrowing traditional, rigid, and centralized approaches to data, and need to explore faster, more flexible, and more democratic frameworks in order to keep innovating and differentiating with data.

What makes a data-driven enterprise?

Is it the amount of data it has at its disposal? The technology it invests in? Is it the way that employees interact with data, or the ‘data vision’ being pushed by senior leaders? Is it the processes that technology teams put in place to govern data as an asset, or is it the business’ overall attitude to data as a resource?

The truth is, it’s none of those things in isolation. A mountain of data doesn’t mean anything if you’re not equipped to use it. A ‘data vision’ is only worth something if you have the means to make it a reality. Processes are meaningless if the people who are supposed to be following them ignore them instead. As for technology – there’s no platform or tool in the world that can tackle every data problem on its own and create a ‘data-driven’ attitude within a business.

That’s why any successful modern data ecosystem needs a combination of technology and culture underpinning it. For an enterprise to become truly data-driven, it needs an ecosystem that has the technical capabilities the business requires to fulfil constantly evolving data goals and empowers every department and division to get value from data.

If you’re looking to modernise your data ecosystem, you need to think not only about the technology it contains but the culture it inspires. Here, we explore the relationship between technology and culture in modern data ecosystems.

What makes a modern data ecosystem?

A modern data ecosystem is defined by several key elements: they’re scalable, sharable, accessible, available, cloud-first, and agile. While this list relates mostly to technology and the capabilities each tool or platform will need as part of your architecture, the behaviors surrounding those technologies are just as important. What good is scalability, if the business doesn’t have the vision to expand its data opportunities? Why make data accessible, if it’s only going to be used by a handful of central data scientists, or one core IT team?

Modern data ecosystems reflect the need for greater accountability and interaction with the wider business, as well as addressing how data can remain interconnected and well-governed across the business. The first step is ensuring you have the technical capabilities within your ecosystem to fulfill those needs.

Technology: the capabilities you need in a modern data ecosystem

A modern data ecosystem is an approach, not a platform. There’s no technology you can ‘buy in’ that will create an ecosystem for you: creating a modern data ecosystem means assessing what capabilities you have and what you need to add or enhance to get your ecosystem to where it needs to be to support your objectives. This combination of technology will differ from business to business, depending on specific goals and technology needs, but it can usually feature the following:

  • Core infrastructure – the platform that underpins your architecture, usually cloud-based.
  • Ingestion– the pipelines that import data from multiple sources.
  • Data storage – a storage solution or solutions: storage can be centralized or decentralized depending on your approach
  • Data integration and virtualization– technology that delivers data to where it’s needed.
  • Data Access – technologies that make data available.
  • Data Governance and management – processes that ensure data, including metadata, is accurate, reliable, secure, and recoverable.
  • Data Catalogue and Enterprise Knowledge graph– an organized inventory of data assets, using metadata to enable context, control, and collaboration.
  • Data security – inbuilt security protocols such as data masking, encryption, and resilience.
  • Modern Business Intelligence (BI) and analytics platforms – provide analytics capabilities to multiple personas across the organization, incorporating augmented analytics and support for decision intelligence.
  • Data Science and Machine Learning platforms – enables delivery of business value through the application of data science and machine learning techniques. Supports democratization of Data Science and Machine Learning across the organization as well as decision intelligence.

Culture: instilling accountability and democracy with data

Even if all of those technologies are present, a modern data ecosystem can only be successful if you have the culture to support it. As mentioned above, a modern ecosystem is about connections, interactions, governance, and accountability as much as it is about tools and platforms.

The success of a modern data ecosystem both depends on the attitudes and understanding of the people utilizing it, and can encourage people to take greater accountability. Broadly speaking, this isn’t really any different from existing data ecosystems: governance has always been critical to making sure that data quality is maintained, while also encouraging more active engagement with data. The difference with a modern data ecosystem is that this accountability and governance is a core part of what knits the entire ecosystem together.

Whether you choose to introduce a well-defined approach like Data Mesh, which by its nature has a strong focus on accountability, or something more flexible, making sure that people take responsibility for data and systems is essential to making a modern data ecosystem work effectively. In turn, this transforms both individual and departmental attitudes to data. People are empowered to use data more creatively and explore their own vision for data, bringing more opportunities with data to the fore throughout the business.

How to introduce a modern data ecosystem

If you’re looking to introduce a modern data ecosystem, don’t throw out the rule book and start from scratch. It’s likely that the foundations of a modern data ecosystem already exist in the technologies and processes you have. To find out more about what it takes to implement a modern data ecosystem, download Amplifi’s guide to modern data ecosystems.