Systems | Development | Analytics | API | Testing

How to optimize your cloud data costs: 4 steps to reduce cloud data platform costs

If you have managed a cloud data platform, you have undoubtedly gotten that call. You know the one, it's usually from finance or the office of the CFO, inquiring about your monthly spend. And it usually comes in one of two forms: While both are clear and present dangers to cloud data platform owners, they don’t have to be.

ThoughtSpot for Google Cloud Platform

ThoughtSpot is partnering with Google Cloud to expand self-service analytics capabilities beyond the dashboards! Now you can use AI-powered search to query Google BigQuery in real-time, access the Looker semantic layer to obtain reliable and standardized data models, and close the productivity loop with ThoughtSpot plugins for Google Sheets, Connected Sheets, and Slides.

What is Product Design? Everything you need to know!

Over the span of a couple of decades, product design has transformed massively. Yet, until lately, it was thought of as a physical and materialistic design, necessitating an experienced individual to work with conventional tools to make something substantial. That era, however, is light years away from how it has evolved in our present-day digital age.

Setting up Google BigQuery as a data warehouse in minutes

In this tutorial, learn how to set up a new Google BigQuery cloud-based data warehouse account and extract data from all your data sources using Stitch in less than 3 minutes. Stitch partners with the most common data warehouses and data lakes to help move your data from sources like Shopify, MongoDB, LinkedIn Ads, Zapier, Hubspot, SendGrid, Google Analytics, and more. Google Analytics. Watch this step-by-step tutorial on how to set up Google BigQuery for data storage.

Kubeflow Vs. MLflow Vs. MLRun: Which One is Right for You?

The open source ML tooling ecosystem has become vast in the last few years, with many tools both overlapping in their capabilities as well as complimenting each other nicely. In part because AI/ML is a still-immature practice, the messaging around what all these tools can accomplish can be quite vague. In this article, we’ll dive into three tools to better understand their capabilities, and how they fit into the ML lifecycle.

Mastering ADB: The Ultimate Guide to Debugging Your Android Applications

Once, your users may have forgiven a bug in your app. Today, they likely won’t. Today’s consumers, many of them Gen-Zers who’ve been using gadgets since they learned their hands, expect a mobile experience that’s swift, seamless and secure. And with page speeds increasing all the time, lags and snags are no longer acceptable. Which means our apps need to glitch-free right out of the gate.

From Kinesis to Kafka

At the beginning of 2021, a brand new data team was assembled to build a real-time data platform for Kong’s SaaS platform, Konnect. Our mission is to provide top-notch real-time API analytics features for Konnect customers. V1 platform architecture The initial backend consisted of three main components: an ingestion service to handle incoming telemetry requests, an intermediate message queue, and a real-time OLAP data storage.

The future of mobile shopping apps: 12 key trends to stay ahead in a world of Super Apps

Despite the prevalence of Super Apps, staying competitive is still possible. By understanding and adapting to the latest trends in e-commerce and m-commerce, you can ensure that your shopping app stays ahead of the game in a competitive market.