The Data Analytics Platform

Towards Data and Analytics Democratization

Nicole Mpozika
Mar 14, 2019 · 5 min read

Today, every business wants to analyse the huge amount of data available in order to create business value. However, data is typically buried across a complex landscape of different departments, source systems and databases. The data and the analytics tooling required to draw insightful business decisions from this data are rarely available in the same environment. Now more than ever there is a need for the democratization of data and analytics; making data and analytics tooling easily accessible to all the people who need it and have the skill-set to analyse it

In order to do this, it is important to centralize the data stores, harmonize data definitions and ensure good governance. This work in building an Enterprise Data Lake is being currently executed by ING’s Chief Data Officer and Data Management organisation. Nevertheless, it is important to reap the benefits of this initiative, delivering services around that data so that people can actually work with it and analyse it. ING WB Advanced Analytics has developed such a platform called the Data Analytics Platform (DAP).

Making the data accessible and understood within the corporation can accelerate decision-making and unleash real-time opportunities for the organisation. We can see many corporations sitting on a goldmine of data but not having the necessary resources to leverage it. To address the challenge, a number of Big Data providers and commercial tools were created to help solve the challenge of working with massive data sets. However, these platforms are not designed to be used by a wide range of user groups — from business users to data scientists -and they are generally not keeping pace with the rapid developments in the fields of machine learning and artificial intelligence.

In order to work towards agility, scalability and real-time efficiency in data analytics, Bolke de Bruin — Global IT Lead in WBAA, Rob Keevil — Lead of the Data Analytics Platform and Krzysztof Adamski — Product Owner of the Data Infrastructure squad — identified the need for a new project to unlock data and analytics within ING — the Data Analytics Platform. Rob explains:

“In addition to allowing us to scale, be more innovative and continue to build powerful AI-driven projects in WBAA going forward; the Data Analytics Platform will allow us to democratize Data Analytics to the wider ING bank. To be able to make data-driven decisions you need three things; sufficient data (with data privacy groundwork to allow you use this data), sufficient processing power to enable you to perform analytics over global-scale data-sets, and access to suitable tooling (software) to enable you to enact your analytics in a way applicable to your skills and business domain. I strongly believe that the DAP is the leading ING platform to provide all three of these elements together in a single environment”.

Kris, responsible for the Data Infrastructure added:

“We all thrive to make ING a data-driven company. We want to speed up the experimentation phase to allow our data scientists to start fast by bringing their own data, but also having access to a curated(data quality metrics) and governed (data-lineage) wealth of data-sets at hand. Of course, this must be done whilst making sure the data is still secured within the platform (via authorization and limited time access). DAP also delivers a powerful processing engine based on Kubernetes (a container orchestration platform) and support for GPUs to make sure only our imagination is the limit, not the infrastructure. Our ultimate goal is to make data available for everyone who needs it to make a business decision within ING. We need to make sure we support these decisions with all the data that is required, up-to-date and accurate”.

Overall, the new Data Analytics Platform that WBAA is working on is expected to:

Allow other teams within the bank to make use of our environments and data (democratizing data, analytics and AI).

Encourage Innovation by allowing more freedom and experimentation in the tools ING are able to use.

Accelerate project delivery by reducing the time investment required to create a product.

Enhance processing capacity by facilitating the rapid expansion of the WBAA team, without a processing performance bottleneck.

Increase resiliency and up-time through end to end use of resilient technologies.

Simplify maintenance and encourage self-service administration of the platform (greater infrastructure team capacity, faster issue resolution).

Elastic scalability (just add new machines for more capacity, future-proofing).

Greater efficiency of the platform (more performance per infrastructure euro spent).

Make WBAA Cloud-ready, so solutions can be deployed on public cloud infrastructure with minimal friction.

Improve security of the platform (moving to the latest standards and best of breed encryption algorithms).

Full data Lineage trace-ability (Knowing exactly where your data came from, and what has been derived from it).

The primary goal of building the Data Analytics Platform is to democratize Artificial Intelligence and Machine Learning for all the layers of ING. We work towards an effective governance of data and analytics by striking a balance between scalability and agility, always maintaining a high level of data security. Recently, Rob and Kris presented the Data Analytics Platform at Warsaw’s Big Data Technology Summit, attaining positive reactions and feedback from a top-notch tech audience.

Rob also represented ING WBAA in a panel discussion on the current megatrends that change the Big Data landscape, with representatives from Google, GetInData and Ververica.

If you wish to learn more on the Data Analytics Platform or on WBAA projects, please send an email at

Wholesale Banking Advanced Analytics team

Nicole Mpozika

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