There is no one-size-fits-all agency business model. 20 agency owners share the pros and cons of their pricing models.

When it comes to app development, low-code is the future. Many companies and organizations are already turning to low-code or no-code solutions for their business-related software needs. While low-code is changing the game when it comes to app development, is low-code really the way to go? And if low-code tools really are the right choice for your organization, how do you go about finding the right platform for your business goals? And what should you even be looking for in a low-code platform?

As Halloween night quickly approaches, there is only one question on every kid’s mind: how can I maximize my candy haul this year with the best possible candy? This kind of question lends itself perfectly to data science approaches that enable quick and intuitive analysis of data across multiple sources.

Analysts and data scientists use SQL queries to pull data from the data storage underbelly of an enterprise. They mold the data, reshape it, and analyze it, so it can offer revenue-generating business insights to the company. But analytics is only as good as the material it works with. That is, if the underlying data is missing, compromised, incomplete, or wrong, so will the data analysis and inferences derived from it.

Tired of spending hours on creating GA reports? Here’s how Google Analytics users can make the most out of automated reports.

When you need to get new features and products out the door fast, API management is the driving force to keeping everything on track. According to the "State of API Integration 2020" report by Cloud Elements, 83 percent of respondents say that API integration has become a critical part of their business strategy as they move forward on their digital transformation efforts. Leveraging integrations is what helps these companies agile and able to respond quickly to customer demands.

By Jean-Baptiste Thomas, Pure Storage & Yaron Haviv, Co-Founder & CTO of Iguazio You trained and built models using interactive tools over data samples, and are now working on building an application around them to bring tangible value to the business. However, a year later, you find that you have spent an endless amount time and resources, but your application is still not fully operational, or isn’t performing as well as it did in the lab. Don’t worry, you are not alone.

There are many good uses of data. With data, we can monitor our business, the overall business, or specific business units. We can segment based on the customer verticals or whether they run in the public or private cloud. We can understand customers better, see usage patterns and main consumption drivers. We can find customer pain points, see where they get stuck, and understand how different bugs affect them.