Russian companies have been building analytics systems mainly using global products for a long time. This determined the architecture of data solutions and teams’ approaches
Category: BIG DATA
Impact Of Big Challenges On The Russian Big Data Market: Expert Opinions
Moving to the cloud and using open-source Changes in the IT market have affected the plans of companies to work with big data. In 2022,
Impact Of Not Preparing Processes For Kubernetes Deployment
Development needs to be adapted for Kubernetes, first implement DevOps processes that affect all code development. And when companies adopt Kubernetes, they often abandon the
Kubernetes – Process Of Preparing For Migration
Regardless of the starting point for migrating to Managed Kubernetes, there is a general list of steps recommended to be performed before starting. Let’s take
An Operational Checklist For Redis In Kubernetes
We translated the checklist for running Redis inside a Kubernetes cluster. It is worth familiarizing yourself with it before moving on to using Redis under
Big Data Technologies: How Big Data Is Analyzed To Get Maximum Profit
Big data is not enough to collect – it needs to be used somehow, for example, to make forecasts of business development or test marketing
Six Takeaways About Kubernetes: What Companies Care About When Implementing This Tool
The challenges of scaling increased uptime and Kubernetes Edge are some of the companies’ challenges. In 2019, the KubeCon + CloudNativeCon 2019 conference was held,
How And Why “Auchan” Built A Platform For Working With Big Data In A Public Cloud
Modern retail can no longer do without building predictive and recommendation systems based on Big Data.But with large amounts of data, such as at Auchan,
Pros And Cons Of AirFlow
Most often, the following advantages of AirFlow: Open-source: AirFlow is supported by the community and has well-documented documentation. Based on Python: Python is considered a
AirFlow: What It Is, How It Works
Data processing in information systems is divided into three stages: extraction, transformation, and loading (Extract Transform Load, ETL). In solutions using Big Data, it is
