On the 26th anniversary of JavaScript, it's hard to fully measure the impact of this "open-source, cross-platform language for enterprise networks and the internet." It has transformed the landscape of computing by becoming the top language in development. Its community has grown significantly and taken a vital role in the evolution and, of course, support of JavaScript. It's a tremendous achievement!
Without users, products mean nothing. So why is it that so many organizations analyze API and user behavior metrics as an afterthought? My theory would be that they just don’t have the right tools in place to actually collect, analyze, and use these usage metrics. With so many products aiming to improve their user experience and customer satisfaction, tools like Moesif are exactly what is needed.
When looking at API analytics and monitoring platforms, many seem to be so similar that it’s hard to figure out the differences between them. We often hear this confusion from users and prospects. In a world with so many tools available, how do we figure out which ones are necessary and which are redundant? One of the most common questions we are asked revolves around how Moesif compares to Datadog and how they could work together.
It takes vision, purpose, and skill to unlock the power of data. It also takes the right strategy. For ExxonMobil, Ares Trading (Merck), and the University of California San Diego (UCSD), the right strategy is taking full advantage of the cloud. All three organizations have partnered with Cloudera, leveraging a hybrid or cloud-based architecture to improve the lives of the people who depend on their organizations’ data.
Organizations in the financial services sector face a unique set of challenges as they consider how to wrangle and process the vast amount of data they collect. During our Financial Services Summit, I was lucky enough to speak to Brian Anthony, chief data officer for the Municipal Securities Rulemaking Board (MSRB), to learn how the MSRB is integrating technologies such as artificial intelligence (AI) and machine learning to modernize its data.
Machine learning (ML) models have become key drivers in helping organizations reveal patterns and make predictions that drive value across the business. While extremely valuable, building and deploying these models remains in the hands of only a small subset of expert data scientists and engineers with deep programming and ML framework expertise.
At Snowflake, putting the customer first is an essential company value. But “customer-centric” is more than just a buzzword: We use a data-driven, outside-in lens on everything we do, at all levels of the company. In particular, here’s how Snowflake Support is listening to you—our customers—and continuously improving the Snowflake customer experience at every touchpoint.
The business world is rapidly pivoting all the time. Strategic shifts, reprioritization and being first all require being smart while moving fast. The value of agility has never stood out more due to the need to react to new realties in everything from public health, remote and in-office business policies and workflows, to broader economic concerns like supply chain as we move into recovery and revitalization.
For any e-commerce business, having an extensive product catalogue with detailed descriptions is essential. If you present your products or services well, there will be more potential customers eager to purchase from you. The biggest issue, however, is usually the fact that you have to create very many product descriptions that are very similar to one another. Making these feels too repetitive and mundane which could lead you to getting tired quickly.
