7 Cryptocurrency Resources to Know If You're Thriving on Online Payments

Online payments are now officially the preferred mode of transaction for a lot of eCommerce and brick-and-mortar stores. In 2020, the transaction value for digital payments globally, crossed $5.2 trillion. Sure, a lot of that can be attributed to the fact that consumers shifted to online purchases due to the pandemic, however, the growth over the years is undeniable.

Crashes in Neobank, eBank, and Crypto-trading Apps Are Unforgivable-Crash Analytics is the Answer

Regardless of how technically sound the engineering of an app is, bugs, errors, and crashes can happen. So when they do, you must recover from it by doing a deep analysis of the technical aspects and the impact on the overall customer experience. If your crypto-exchange or banking app is not getting the right insights you need from the crashes, your churn rate and your customers will definitely let you know sooner than you think.

Why Is Your Crypto App Not Measuring NPS (Properly)?

Crypto trading and exchange apps have surged in recent years as a direct consequence of the exponential growth in the number and market capitalization of cryptocurrencies. With ever-growing press coverage and heightened visibility, the crypto ecosystem gets more and more crowded every second. This constant influx of players has clearly been beneficial, as the assets traded continue to grow.

Introducing six new cryptocurrencies in BigQuery Public Datasets-and how to analyze them

Since they emerged in 2009, cryptocurrencies have experienced their share of volatility—and are a continual source of fascination. In the past year, as part of the BigQuery Public Datasets program, Google Cloud released datasets consisting of the blockchain transaction history for Bitcoin and Ethereum, to help you better understand cryptocurrency. Today, we're releasing an additional six cryptocurrency blockchains.

How we built a derivatives exchange with BigQuery ML for Google Next '18

Financial institutions have a natural desire to predict the volume, volatility, value or other parameters of financial instruments or their derivatives, to manage positions and mitigate risk more effectively. They also have a rich set of business problems (and correspondingly large datasets) to which it’s practical to apply machine learning techniques.

Ethereum in BigQuery: how we built this dataset

In this blog post, we’ll share more on how we built the BigQuery Ethereum Public Dataset that contains the Ethereum blockchain data. This includes the primary data structures—blocks, transactions—as well as high-value data derivatives—token transfers, smart contract method descriptions.

4 Possible Ways a Blockchain Can Impact Data Management

We all know we are at the peak of the hype cycle for…wait for it – Blockchain! We are also already aware of some of the benefits of blockchain - but can blockchain be applicable to traditional data management? Though real-world blockchain implementations in the enterprise are minimal so far, I do believe there is a ton of potential to solve some of the problems that businesses face.