Big Data

When your systems work, everything is okay, but when something fails, you need to analyze the logs. We explain the importance of analyzing the server logs.

Selecting the right approach to building distributed data pipelines requires finding a good managed cloud computing solution, so we compare Google Cloud Compose with Astronomer.

You have definitely heard about DevOps transformation and the benefits it can bring to your business. You know it all, yes? About cost-reduction due to transition to the cloud platforms, streamlined software delivery and reduced time-to-market due to implementation of CI/CD (Continuous Integration / Continuous Delivery) workflows and a general increase in productivity due to DevOps culture of collaboration and communication between teams.

While 2018 is quickly coming to an end, data scientists and analysts worldwide look around to see what trends dominated the Big Data landscape and to learn the results of the business implementation of Big Data solutions.

The banks are meant to be the stewards of the customers’ money, yet after the financial crisis of 2008 quite a few people don’t trust them. Here is how Big Data can help the banks regain the customer’s trust.

Digital transformation is a process of integrating the latest technology to ensure maximum efficiency and competitiveness of existing workflows. Cloud, DevOps and Big Data make it happen.

Big Data Analytics can become the main driver of innovation in the banking industry — and it is actually becoming one. We list several areas where Big Data can help the banks perform better.

2018 might well become the year of huge leaps in predictive analytics, AI, edge computing, data storage, hybrid cloud and much more… Learn about the hottest IT trends for 2018!

Correct use of the Big Data analytics and ML algorithms helps boost the customer satisfaction, secure the bottom line and increase the ROI. Quite opposite, the Big Data misuse results will be awful.

What is web scraping? It is essential for gathering Big Data sets, which are the cornerstone of Big Data analytics, Machine Learning (ML) and tutoring the Artificial Intelligence (AI) algorithms.