adesso BLOG

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.

In an increasingly digitalised world, the systematic collection, interpretation and use of data is becoming a factor in success. If a company fails to do this, it will lose a key tool needed to stay competitive and innovate in the age of digitalisation. In my blog post, I explain why data governance is important for companies and how adesso can support them in this area.

A data lake, also known as a data platform, is an ingenious and highly effective solution for addressing the complex challenges that come with storing, managing and analysing vast quantities of data. It provides an advanced infrastructure that enables organisations to store data in its native form and be flexible with how they process it later. In my blog post, I will go through the advantages it brings to the table.

Apache Hudi, Iceberg and Delta Lake have proven to be powerful tools that are revolutionising the way modern data platforms handle data management and analysis. In my blog post, I will discuss the core features of these data types and highlight their respective strengths and applications.

The era of digitalisation has seen the amount of data available increase exponentially. That is why good communication between instances is still the key to managing it – and data standards play a major role in this. This blog post will explain which challenges data standards can solve.

While the first part of my blog series focused on the technology of NB-IoT, the second part will discuss the technical aspects of using it, as the advantages of transmitting data using narrowband IoT are quickly squandered if it is used incorrectly.

Just survived your annual sustainability reporting round? ESG data gathering can be an extensive and exhausting effort, but yearly results still may be based on estimates and require manual data collection. Sustainable data roadmap is a systematic tool to tackle these challenges and get real value out of your sustainability data.