Systems | Development | Analytics | API | Testing

Developing More Accurate and Complex Machine-Learning Models with Snowpark for Python

Sophos protects people online with a suite of cybersecurity products. Hear Konstantin Berlin, Head of Artificial Intelligence at Sophos, explain how the Snowflake Data Cloud helps Sophos increase the accuracy of their machine-learning models by allowing data scientists to process large and complex data sets independent of data engineers. Through Snowpark, data scientists can run Python scripts along with SQL without having to move data across environments, significantly increasing the pace of innovation.

3-Minute Recap: Unlocking the Value of Cloud Data and Analytics

DBTA recently hosted a roundtable webinar with four industry experts on “Unlocking the Value of Cloud Data and Analytics.” Moderated by Stephen Faig, Research Director, Unisphere Research and DBTA, the webinar featured presentations from Progress, Ahana, Reltio, and Unravel. You can see the full 1-hour webinar “Unlocking the Value of Cloud Data and Analytics” below. Here’s a quick recap of what each presentation covered.

Get Ready for the Next Generation of DataOps Observability

I was chatting with Sanjeev Mohan, Principal and Founder of SanjMo Consulting and former Research Vice President at Gartner, about how the emergence of DataOps is changing people’s idea of what “data observability” means. Not in any semantic sense or a definitional war of words, but in terms of what data teams need to stay on top of an increasingly complex modern data stack.

Ep 59: New Zealand's Crown Research Institute CDAO, Jan Sheppard on Treating Data as a Treasure

Treating data as a treasure is a foundational principle for Jan Sheppard, the Chief Data and Analytics officer at New Zealand’s Crown Research Institute of Environmental Science and Research (ESR.) This agency leads ongoing research in public health, environmental health, and forensics for the country of New Zealand. Like many other CDAOs, her role is relatively new. But the unique values she applies to data can be traced back many hundreds of years to the indigenous Maori people of her country. Through her work, Jan recognizes the profound impact data can have on people and their environments for generations to come.

Integration testing made easy with Oleg Šelajev | Kongcast Episode 21

In this episode of Kongcast, @Viktor Gamov , a principal developer advocate at @Kong joined by @Oleg Šelajev , Head of DevRel at @AtomicJar to talk about testing complex infrastructures (data systems, microservices, messaging systems) using containers, and specifically open source library called Testcontainers.

What Challenges Are Hindering the Success of Your Data Lake Initiative?

Conventional databases are no longer the appropriate solution in a world where data volume is growing every second. Many modern businesses are adopting big data technologies like data lakes to counter data volume and velocity. Data lake infrastructures such as Apache Hadoop are designed to handle data in large capacities. These infrastructures offer benefits such as data replication for enhanced protection and multi-node computing for faster data processing.

7 Best Data Pipeline Tools 2022

The data pipeline is at the heart of your company’s operations. It allows you to take control of your raw data and use it to generate revenue-driving insights. However, managing all the different types of data pipeline operations (data extractions, transformations, loading into databases, orchestration, monitoring, and more) can be a little daunting. Here, we present the 7 best data pipeline tools of 2022, with pros, cons, and who they are most suitable for. 1. Keboola 2. Stitch 3. Segment 4.