Systems | Development | Analytics | API | Testing

Build limitless workloads on BigQuery: New features beyond SQL

Our mission at Google Cloud is to help our customers fuel data driven transformations. As a step towards this, BigQuery is removing its limit as a SQL-only interface and providing new developer extensions for workloads that require programming beyond SQL. These flexible programming extensions are all offered without the limitations of running virtual servers.

Build data apps with Streamlit + ThoughtSpot APIs

I’ve been following the Streamlit framework for a while, since Snowflake announced that they would acquire it to enable data engineers to quick spin up data apps. I decided to play around with it and see how we could leverage the speed of creating an app along with the benefits that ThoughtSpot provides, especially around the ability to use NLP for search terms. Streamlit is built in Python.

Coherent Automates The Capture Of Spreadsheet Logic

Coherent Spark solves a common problem plaguing millions of Excel spreadsheet users: How to easily capture spreadsheet logic and bring it into the cloud to integrate it with modern systems? In this episode of “Powered by Snowflake,” Coherent Spark CTO Peter Roschke explains how the Spark platform takes advantage of the processing power of Snowflake to tackle that challenge. With Spark, the logic of Excel spreadsheets of any size or complexity, including enormous legacy spreadsheets containing millions of formulas, can be converted quickly into a cloud-compatible format capable of driving applications for all types of use cases.

Planetly: Scaling companies' carbon management with data

Planetly uses technology to simplify carbon management for companies at scale. Their data-driven software solution helps companies reach net-zero emission targets in four steps: The entire carbon management life cycle is powered and fueled by data. We talked to Cari Davidson, VP of Engineering and Patricia Montag, the Engineering Lead Analytics, to better understand what role Keboola (and data as a whole) play in the company’s operations and what that means for the engineering team.

Cybersecurity: A Big Data Problem

Information technology has been at the heart of governments around the world, enabling them to deliver vital citizen services, such as healthcare, transportation, employment, and national security. All of these functions rest on technology and share a valuable commodity: data. Data is produced and consumed in ever-increasing amounts and therefore must be protected. After all, we believe everything that we see on our computer screens to be true, don’t we?

Diving Deep Into a Data Lake

A Data Lake is used to refer to a massive amount of data stored in a structured, unstructured, semi-structured, or raw form. The purpose is just to consolidate data into one destination and make it usable for data science and analytics algorithms. This data is used for observational, computational, and scientific purposes. The database has made it easier for AI models to gather data from various resources and implement a flawless system that can make informed decisions.