The 8 characteristics of a successful data product

The data mesh architecture is built around four fundamental concepts, the second of which is "data-as-a-product" often just called data products.

Read more

Digazu for the automotive industry

Read about the 2022 latest trends and use cases shaping the new automotive industry.

Read more

The real-time data revolution

IT-powered innovations, the Internet of Things and new generation customer demands are fueling real-time data creation. In this new data landscape, businesses from all industries are quickly shifting from batch processing to real-time data streams to match the new imperatives. In this blog, our marketing analyst, Selima Triki, unpacks the concept of real time and real-time data, some of its benefits and applications.

Read more

No-code/low-code and Virtualisation for efficient Data Engineering

In this blog, we uncover the multiple facets of data engineering, what it is and how complex it can be. Digazu's product manager, Luc Berrewaerts walks us through the new technologies to navigate the complexities of data engineering.

Read more

Six important trends of the 2022 data and analytics landscape

Our CEO shares his thoughts on the 2022 most defining trends of the data and analytics market.

Read more

Migrating a thousand data pipelines thanks to code as configuration

A leading investment bank approached us recently to review their data management to support new analytics use cases. Learn about how we helped them enhance their data processes through automation and scalability.

Read more

The 4 Most Common Mistakes of Digital Transformation Programs

Read our latest White Paper on the most common mistakes of digital transformation programs, the dos and don'ts of the data journey. Come take a closer look at some of the most challenging pitfalls businesses regardless of their space face in their pursuit of digital and capture the best practices and lessons learned to to drive successful data projects.

Read more

Implement the right data storage architecture, build your business for the future

Learn the various ways in which you can store your data and choose the one that best suits your needs. This article will underline the difference between data warehouse, data lake and data mesh while exposing the benefits and drawbacks that you could encounter. Find the best solution no matter how mature your data is.

Read more

Data processing: simplified integration of your data

In this article we are focusing on a crucial step in adapting better data practices: data processing. Use your data to its fullest by properly managing how you store the data so that it is readily available any time you need to make a decision.

Read more

Data preparation, the pre-processing stage that slows you down

Overlooking the basic stages of the data journey happens very often which results in severe delays of ML and deep learning projects. This article shines the light upon the main players in the 80/20 data Science dilemma: data preparation. Find out how to make sure that your data scientists and ML experts uncover insightful value from your data in the shortest time possible.

Read more

Data collection, a first step in maximising the value of your data

Pushing the limits of your data doesn’t have to be a difficult task. Still, if left alone, data has little to no value. Read this article and bring your data to life by taking proactive actions towards understanding how to overcome the challenges that data collection can pose. Sometimes simple solutions can solve complex problems.

Read more

The New Data Engineering

Discover how you can take your data engineering to a whole new dimension with Digazu. Specifically designed to simplify the work of your data engineers, Digazu was built to work at scale and to integrate with your IT landscape for sustainable and scalable data engineering.

Read more

What happens if you implement a business case roadmap without a platform strategy

Implementing your business cases comes with a price tag of high expectations and inevitable costs. Read this article and discover how you can drastically control the cost of implementation of your use cases and reduce your projects’ time to market.

Read more

A glimpse into a great data platform

Discover the building blocks of a modern and scalable data platform. Get insights on how to power your data projects and unlock the value of your data assets.

Read more

A full-scale industrial roll-out at a large automobile manufacturer

As a leader within a very competitive industry, our customer saw very early the potential of using data to improve production efficiency and create the best possible customer experience. One important step in that journey was the decision to create a pan-European Data Analytics landscape.

Read more

What happens if (3/4): You take IT initiatives without onboarding the business department

Read about the impact of IT and business misalignment on the organisation's overall success. We share our tips on how to bridge the Tech and business gap.

Read more

What happens if (2/4): You take business initiatives without onboarding the IT department

Learn more about the common mistakes of digital transformation programs: taking business initiatives without onboarding the IT department.

Read more

What happens if (1/4): You underestimate the complexity of the underlying technology of a modern data platform

Discover the challenges and consequences of the companies that are underestimating the complexity of a modern data platform.

Read more

Low-code platforms vital for the company's success

Digazu's Low-code platforms will help you address all your data and data processes challenges in a sustainable and future-proof way. Easy-to-use and highly intuitive, Digazu combines the power of automated data engineering, a data lake and a smart data-science platform.

Read more

Data-driven organization and data silos

Discover how data-driven business and data silos cascades all the way down from the different data choices, uses and strategies that companies are using

Read more

What are the challenges of data silos and how can I manage them?

A feature-rich data science platform can help you navigate through data silos and bring holistic data management into your organization and leverage the highest possible value out of it.

Read more

Become a data-driven business and avoid data silos

Surviving as a mainstream business today means being data-driven. Yet, becoming a data-driven organization does not happen overnight, it takes a lot more than a few resolutions and a well-articulated data strategy.

Read more

How to secure your data lake projects

Discover how to secure your data lake projects to help your company leverage its produced data to create revenues and reduce its costs.

Read more

Challenges of data lake project and how to minimise the failure risk

To help you drive a successful data lake project you have to discover what are the challenges in a data lake project, and how you can minimise the failure risk.

Read more

What are the benefits of a data lake?

A data lake will help you leverage all your produced data to create revenues and reduce your costs. So you have to ask yourself why would my company need a data lake and what are my benefits from setting up a data lake?

Read more

Facilitate and optimize the work of your data-engineers.

Companies need solutions that help real-time data management platforms designed in such a way that extracting data sets is quick, easy and reduces the work of IT teams.

Read more

Discover the pathway of GDPR compliance through Data

Download the white paper to discover how to successfully introduce organizational GDPR changes and its requirements to install an effective data governance tool to help you embed privacy into your everyday work.

Read more

A Tailored Shopping Experience, or How to Display Custom Content in Real Time

Companies need solutions that aggregate many sources of on- and off-line information, extract data sets quickly, and ease the deployment of models to compute real-time compelling recommendations.

Read more

Digazu answers the banking sector challenges

Discover how can Digazu help the banking sector dealing with real-time banking transactions and streamlining data between data producers and data consumers.

Read more

Real-time recommendation challenges for intermediaries

Generate, trough data, additional revenues by automating recommendations with intermediaries, making targeted interactions with customers possible.

Read more

Improve your marketing processes and customer satisfaction

Match your business with the everlasting changes in customers’ preferences and expectations.

Read more

Customer experience with a multichannel real-time data approach

Discover how to add value to your retail business and to personalize each customer engagement trough by integrating a multichannel data approach across your real-time reporting and your data science models.

Read more

Digazu helps you answer the ETL challenges

Digazu helps companies leveraging the value of their data, by extracting data only once, sharing the transformations on data, and loading transformed data multiple times.

Read more

The challenges of ETL and their related data-driven business ambitions.

Today’s business are trying to become more data centric or to develop their data culture. To do so they have to start leveraging insights from their data. Therefore, ETLs (extract, transform, and load) are essential in data integration strategies.

Read more

Data challenges across companies

Data challenges across companies and departments; time-to-market, cost and feasibility of your data science projects all depend on your processes and tools.

Read more

Purpose of Digazu

Digazu was made to create added value for companies from their data and make complex data engineering easier and Faster.

Read more

Demo real-time product recommendation

Discover, through this demo, a fast and easy way to create real-time product recommendations with our Digazu's end-to-end data engineering platform.

Read more

Fraud detection

By using Digazu you will significantly reduce the time to implement all the necessary steps to detect potentially fraudulent behaviour.

Read more