HubSpot is a customer relationship management (CRM) platform that helps you capture all of your interactions with customers and potential customers, from their first call or website visitors to their most recent purchase. With tens of thousands of users around the world, HubSpot currently owns an estimated 30 percent of the global CRM market share.

Developing a content strategy might seem like a full-time job. It can be a bit daunting to a small business owner who is just starting out. The good news is, you don’t have to spend several hours every day creating new content to post on your blog or social media accounts. There are simple ways to create a content marketing strategy that works best for your business needs. However, it starts with having the right set of digital tools.

Symbol tables are an important data structure created and maintained by compilers to store information associated with identifiers . A simplified representation of a symbol table entry (or simply, a symbol) in Java has the following format: .

Optimizing your SEO analytics reporting doesn’t have to be hard. Find out how you can streamline the whole process with the right tools, tips, and tricks.

For our latest specialist interview in our series speaking to technology leaders from around the world, we’ve welcomed Bill Kunneke, Chief Technology Officer at Leasecake. Bill has over twenty years of experience as an IT professional and a proven technical leader who delivers large and often transformative IT projects while communicating complex technical solutions to key stakeholders and executing strategic IT functions.

So you want to move data to Amazon Redshift? You're not the only one. Every day, thousands of organizations worldwide migrate data to Redshift, which Amazon claims is the world's fastest cloud data warehouse. These organizations have one mission: To move data to Redshift so they can generate business intelligence (BI) from the latest metrics. Amazon's data warehouse makes it easy to produce metrics that power data-driven organizations like yours.

As the enterprise IT landscape becomes larger and more complex, many organizations are finding it difficult to manage all of their systems and services. According to a study by the access management company Okta, businesses use an average of 73 different enterprise software applications — and 1 in 10 businesses use more than 200 apps. On-premise business APIs can help connect these applications, but they come with several noteworthy drawbacks.

Advances in the performance and capability of Artificial Intelligence (AI) algorithms has led to a significant increase in adoption in recent years. In a February 2021 report by IDC, they estimate that world-wide revenues from AI will grow by 16.4% in 2021 to USD $327 billion. Furthermore, AI adoption is becoming increasingly widespread and not just concentrated within a small number of organisations.

In my main position, as a data scientist at SIL International, I work on expanding language possibilities with AI. Practically this includes applying recent advances in Natural Language Processing (NLP) to low resource and multilingual contexts. We work on things like spoken language identification, multilingual dialogue systems, machine translation, and translation quality estimation.

This post does not look at a particular aspect of JMeter nor does it give a detailed overview of how to use a particular tool that will compliment your performance testing with JMeter. What it is about is the principles of push to production pipelines and performance testing and while I have stated that this post is not specifically about JMeter in my experience JMeter is one of the best performance testing tools for this type of pipeline integration.