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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 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 (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

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 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 (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