The arrival of more and more data in all segments of the enterprise started out as an embarrassment of riches, but quickly transformed into something close to a nightmare of dark data. However, a raft of new technologies and the processes embodied in DataOps are charting a path forward in which a much higher percentage of data becomes useful. The challenge most companies face is how to manage and get access to all the data flooding in from all directions.

For a long time, many in the analytics and business intelligence (BI) industry, including most of our competitors, have loosely labelled data visualization in the form of charts and dashboards as ‘data storytelling’.

In this episode of Data+AI Battlescars, Sandeep Uttamchandani, Unravel Data’s CDO, speaks with Samir Boualla, CDO at ING Bank France, one of the largest banks in the world. They cover his battlescars in Driving Data Governance Across Business Teams and Building Data Products. At ING Bank France, Samir is the Chief Data Officer. He’s responsible for several teams that govern, develop, and manage data infrastructure and data assets to deliver value to the business.

The acronym ACID stands for atomicity, consistency, isolation, and durability. These describe the set of properties of database transactions that guarantee data integrity despite errors, system failures, power failures, or other issues.

Should your data team focus on business problems and use cases, or expand into more complex areas like predictive analytics?

Not sure whether SQL or GUI transformations are better for your business? Here are the pros and cons of each approach.

With Databox, Monograph moved from a manual process of tracking data to a strategic approach that saves them time, tracks more data and makes improvements.

This article is a step-by-step guide with hands-on tips for migrating your Flutter apps from Jenkins to Bitrise, quickly and easily.

We are roughly a decade removed from the beginnings of the modern machine learning (ML) platform, inspired largely by the growing ecosystem of open-source Python-based technologies for data scientists. It’s a good time for us to reflect back upon the progress that has been made, highlight the major problems enterprises have with existing ML platforms, and discuss what the next generation of platforms will be like.

Every organization wants to stay on the cutting edge of technology, making smart and data-driven decisions. However, ensuring that company information and data integration remains up to date can be a very time-consuming process. That is where CDC can make all the difference. Change data capture or CDC allows for real-time data set changes, ensuring that company data is always up to date. Change data capture can transform the way companies make data-driven decisions.