adesso Blog

Data is the basis for informed decisions. In the past, decisions were often made based on gut feeling. Today, data-driven approaches enable informed bottom-up decisions. However, it is only with well-thought-out visualisation that this data can reach its full potential. This blog post explains why dashboards play a crucial role in this context.

The path to complete decarbonisation will also have a massive impact on gas network operators: parts of the infrastructure will probably no longer be needed in the long term, while other parts will have to be upgraded for operation with hydrogen. In this blog post, we outline a procedure for preparing the switch to hydrogen. The data required for this can also be used for other purposes.

Change Data Capture (CDC) is a technique that captures all data changes in a data archive, collects them and prepares them for transfer and replication to other systems, either as a batch process or as a stream. This blog post focuses on the application of CDC in data lakehouses using the example of Change Data Feed, a variant of CDC developed by Databricks in the context of delta lake-based data lakehouses.

Every day, employees struggle with manual reporting processes that cause high personnel costs, limited opportunities for process optimisation and quality deficiencies. Despite the crucial importance of KPIs for management, manual reporting processes are widespread in production. In this blog post, I explain why companies in the IIoT sector are starting with production reporting.

Metadata-driven data pipelines are a game changer for data processing in companies. These pipelines use metadata to dynamically update processes instead of manually revising each step every time a data source changes. As with data pipelines, metadata maintenance can be a bottleneck in the maintenance and further development of a pipeline framework. In this blog post, I use practical examples to show how the Jsonnet template language makes it easier to maintain metadata.

Workflow orchestration and workflow engines are crucial components in modern data processing and software development, especially in the field of artificial intelligence (AI). These technologies make it possible to efficiently manage and coordinate various tasks and processes within complex data pipelines. In this blog post, we present Prefect, an intuitive tool for orchestrating workflows in AI development.

Snowflake plays a prominent role in shaping the face of the industry in the ever-evolving world of data analytics and data management. This blog post looks at the development of Snowflake and why it is considered a ground-breaking solution for businesses.

Before the introduction of computers, companies used account books, inventory lists and intuition to record key figures. The data warehouse for static reports emerged at the end of the 1980s. Digitalisation brought new challenges. Big data overwhelmed traditional data warehouses, which is why companies introduced data lakes, which also had an impact on the architecture and concepts of analytics systems. The first part of this blog post is about their development, the reasons for their emergence and the problems they solved.

In Part 1 of the blog post, we looked at the basics of data warehouses and data lakes to understand their benefits and limitations. This part is about the evolution to a hybrid solution - the data lakehouse. From the two-tier architecture to the emergence of the lakehouse concept, this part takes us through the evolution of data structures. Learn how the lakehouse combines the strengths of data lakes and warehouses to address today's data-driven challenges.