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Data Engineering

What is Data Engineering?

The purpose of Data Engineering is to aggregate, merge, clean, transform and move data from different sources. This allows you to use the data as a single source of truth across the entire organization. Data Engineering enables you to respond quickly to ever-growing wishes regarding data and provide valuable insights. Having a single source of truth also makes it much easier to keep business logic consistent and track your data.

Why is it important?

Every day we produce 2.5 quintillion bytes of data. In other words, the volume of data is growing at an unbelievable rate. At the same time, you have many different source systems ranging from “on-premise” systems to solutions that run in the cloud. In addition, you often have all kinds of external data sources used in the decision-making process. To ensure that you can provide business processes with the correct and complete data, it is necessary that data from different systems are linked together. It is also important that the organization uses the same information everywhere. Data Engineering offers you the link between data sources and creates a single source of truth.

Rockfeather and Data Engineering

At Rockfeather, we ensure that all your data is up to date and available, creating a single source of truth for your organization. We differentiate between horizontal and vertical integration. Horizontal integration, for example, is moving data from your CRM application to your ERP application; this often is an event-driven process of moving data at the core of your company’s business. Vertical integration is moving data from your CRM application to a SQL Server to prepare the data for Data Visualization or Predictive analytics. These types of integrations refresh data more in bulk mode at set times during the day. We use a wide set of tools such as Azure Data Factory, Logic Apps, TimeXtender, and more. Do you want to know the difference between horizontal and vertical integration tools in the Microsoft portfolio? Have a look at this blog.

Our tools and standards

We use a best-in-class portfolio of toolsets. We continuously evaluate our portfolio and add new and promising solutions to our portfolio. Our current portfolio includes the following:



In short

To be ready as a company to make truly data-driven decisions, having the right Data Engineering layer is essential. A good Data Engineering layer is flexible so that you can respond to changing sources and wishes and, at the same time, offers you the proper governance and structure.

Our Data Engineering Portfolio

Cases & Solutions

data-driven insights ADO Den Haag

Data-driven insights with dashboards at ADO Den Haag

As a football club, ADO Den Haag is known for its green and yellow colours and the characteristic stork. However, what many people do not know is that behind the scenes ADO Den Haag is undergoing a true data transformation. The club wants to gain more insight into its performance through data, so that it can better anticipate and steer. The first step is the automation of manual overviews and the creation of dashboards in Power BI.

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Data-Driven ISS - Rockfeather

Data-Driven Account Management at ISS

ISS-Facility Services want to become the best service provider in the world. To become the best, they want to work with a number of its key-accounts based on a new business model, in which cooperation between partners is central.

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All cases