Data Integration
What is data integration?
The purpose of data integration is to merge data from different sources. This allows you to use the data unambiguously and analyze it in a uniform way. Data integration enables you to respond flexibly to the ever-growing wishes regarding data. At the same time, you can keep an eye on the right governance and the application of consistent business logic.
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 also have all kinds of external data sources that are 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 integration, therefore, offers you the link between data sources and the necessary unambiguity of the data.
Rockfeather and data integration
At Rockfeather we ensure that all necessary data from the various sources is made accessible for you and is connected to one Data Hub. We do this, for example, by means of Azure Data Factory. But we can also ensure that these different source systems are linked with each other via Azure Analysis Services.
In addition, we work from these integration solutions together with other Microsoft solutions such as Logic Apps.
Toolsets 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:
In short
To be ready as a company to make truly data-driven decisions, having the right data integration layer is essential. A good data integration layer is flexible so that you can respond to changing sources and wishes and at the same time offers you the right governance and structure.
Ons Data Integratie Portfolio
Azure Data Factory
Azure Data Factory is a cloud based ETL and data integration service that enables data to be moved and transformed. Using Azure Data Factory, you can move data from many different sources and systems. If necessary, you can also transform the data and write it to a central point. This can then be monitored and properly maintained
Alteryx
Changing business through data science and analytics, Alteryx lets everyone in an organization feel the thrill of getting to the answer faster. The new, end-to-end analytics platform empowers analysts and data scientists alike to create, share, and prep data, perform analysis – statistical, predictive, prescriptive, and spatial – and deploy and run analytic models.
Python
This language is open-source, interpreted, and high-level language that provides an excellent approach for object-oriented programming. It is one of the best tools used by data scientists for various data science projects/applications. It provides great functionalities to deal with mathematics, statistics, and scientific functions.
Cases & Solutions
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.
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.