Systems | Development | Analytics | API | Testing

How to replicate SAP data in BigQuery

Are you interested in unlocking advanced analytics by replicating SAP data into BigQuery? In this video, Lucia Subatin, a Technical Lead in Solution Engineering, will demonstrate how to download and implement an ABAP enhancement built by Google Cloud to stream data directly into BigQuery. Watch, follow along, and ask questions in the comments below! Chapters: product: Cloud - General; fullname: Lucia Subatin;

Talend's acquisition of Gamma Soft offers exciting new capabilities for our customers

I am so pleased to announce that Talend has acquired Gamma Soft, a change data capture market innovator. This is a significant enhancement in the capabilities Talend can provide its customers and partners. Talend’s company vision is to take the work out of working with data, and we're thrilled to add Gamma Soft’s technology to our offerings to do this. Change data capture (CDC) technology is highly sought after by many companies.

FinTech Companies Thrive and Innovate with ChaosSearch

Welcome to the second installment of our ChaosSearch for FinTech blog series, where we explore how financial technology (FinTech) companies can solve analytics challenges and drive business outcomes with ChaosSearch. In Part One of this series, we brought you an in-depth look at how FinTech companies could accelerate application development and streamline operations in the cloud by adopting ChaosSearch for log analytics at scale.

Revolt BI: Implementing Keboola results in a 20x faster data simulation model, 3-5% revenue increase, or even identifying 815,000 EUR of savings

Revolt BI is a consultancy and data implementation agency that provides comprehensive business intelligence solutions for companies of all sizes, by implementing best-of-breed solutions available on the market. For DataOps, they swear by Keboola to bring all the data neatly together and to automatically process it according to the needs of their clients which in total have over 6,9 billion dollars in revenue combined.

What defines the modern data stack and why you should care

When I was working at Google back in the mid 2000’s, we dealt with tens of billions of ad impressions a day, trained several machine learning models on years worth of historic data, and used frequently-updated models in ranking ads. The whole system was an amazing feat of engineering and there was no system out there that was even close to handling this much data. It took us years and hundreds of engineers to make this happen, today, the same scale can be achieved in any enterprise.