Česká spořitelna is the biggest Czech retail bank with 4.5 million clients across 400 branches. Running a bank of this size brings its own data challenges from strict regulatory compliance via a wide range of data management needs, to almost limitless product possibilities within the data-rich environment.

ClearML is an open source MLOps platform, and we love the community that’s been growing around us over the last few years. In this post, we’ll give you an overview of the structure of the ClearML codebase so you know what to do when you want to contribute to our community. Prefer to watch the video? Click below: First things first. Let’s take a look at our GitHub page and corresponding repositories. Later on, we’ll cover the most important ones in detail.

According to IDCs Global Datasphere, 64.2 ZB of data was created in 2020 alone. This number is projected to grow by 23% annually from 2020-2025. Therefore, we need data governance frameworks for efficient data management and control. This will help us extract maximum value out of such high volumes of data. Such frameworks would be required for data integrity, data protection, and data security. Indeed, according to BDO, the average data breach cost has been estimated to be around USD 3.8 million.

Effective control and governance over your data assets is vital for long-term business success. By keeping your data available, reliable and usable for analysis, consumption and sharing, you can ensure data quality, data security and data reliability is consistently met. However, many organizations today struggle to implement governance frameworks over their data, which has once again highlighted the importance of data governance. So, what is data governance?

We asked 70+ marketers to weigh in on the most important blog KPIs. They shared 28 different KPIs that help you measure progress toward all of your goals.

Business processes such as order-to-cash are critical to organizations, particularly for the retail and manufacturing enterprise. And SAP contains valuable data related to the process such as sales orders, distribution, and financial data.

A/B testing is the most effective way to observe users’ behavior with two or more different versions of the same screen or in-app experience. It can help you test variations of an item, generally UI based, to determine which one performs better. Directing some users to version A and others to version B allows you to observe user behavior for each.

Just one pre-written line of code for each data source is all that is needed to orchestrate automated data ingestion effectively.