Systems | Development | Analytics | API | Testing

Technology

Make the Leap to AI Driven Data Applications

The start of a new year is a perfect time to reflect on what was accomplished and look forward, re-evaluate what we can do better. Change, although difficult at first, can also be very rewarding. That’s why I was excited to see similar sentiments shared at Thoughtspot beyond.2021 to move beyond the traditional dashboards of the past.

SaaS in 60 - New Qlik Application Automation Connectors

Recently we added some Data Warehouse connectors for Amazon Redshift, Google Big Query and Snowflake allowing your workflows to utilize data management operations such as inserts, deletions, updates, SQL queries and even API requests. We’ve also added a connector to work with our new automated machine learning environment AutoML as well as a number of remote application and event management connectors that work with Dbt, UI Path and Splunk.

Expanding the Data Cloud with Apache Iceberg

The Snowflake Data Cloud is a powerful place to work with data because we have made it easy to do difficult things with data, such as breaking down data silos, safely sharing complex data sets, and querying massive amounts of data. As customers move to the Data Cloud, their needs and timelines vary—our goal is to meet every customer where they are on their Data Cloud journey.

Amazon Redshift: Comprehensive Guide

As the business world increasingly becomes dependent on technology, the way in which companies handle and store their data becomes even more important. Therefore, finding a safe and secure place to store company data is becoming a necessity in the digital age. One robust cloud data warehouse that has been helping many companies safely store their data is known as Amazon Redshift.

Growing AI Fast with ML-Ops: Breaking the barrier between research and production

AI models get smarter, more accurate, and therefore more useful over the course of their training on large datasets that have been painstakingly curated, often over a period of years. But in real-world applications, datasets start small. To design a new drug, for instance, researchers start by testing a compound and need to use the power of AI to predict the best possible permutation.

Building innovative and secure financial services that help users save money

In this interview, we talked to Sudeep Sidhu, Neo Financial's Lead Mobile Engineer about how to provide better features for users, how to ensure the highest levels of security in fintech app development, and what the future of mobile finance and banking looks like.

3 Ways to Extend Your AWS Capabilities in 2022

Amazon Web Services (AWS) has millions of customers, making it one of the most popular cloud platforms in the world. With over 200 services from data centers globally — compute, storage, databases, machine learning, artificial intelligence, data lakes, analytics, Internet of Things, etc. — AWS makes it easier for businesses to move applications to the cloud and streamline workflows. Still, many gaps exist in native AWS tools, which can limit your company’s AWS capabilities.

How to fit agile methodologies into the constraints of fintech app development? - featuring N26

We talked to Dama Damjanović, Principal Engineer at N26 about how the regulations in finance and banking affect engineering teams behind fintech apps, how they can improve security, and what type of new technology will add the most value to the industry in the coming years.