Systems | Development | Analytics | API | Testing

Visualizing data is an important aspect of presenting insights clearly. But it's not always easy to create an effective visualization that people will understand on their first glance, or even second. So how do you create the kinds of graphs and tables that leave key stakeholders thinking, " Wow! I need this information!" In this post, we will discuss the top nine best practices for data visualization.

More data is available than ever, challenging organizations to change how they interact with their data so they can get the most out of it. Ahmed Munir, Lead SAP Functional Technology Architect Manager at Whirlpool Corporation, has 16 years of SAP leadership experience. He joins us to share what he has learned about building great data teams, upcoming trends in data analytics to keep an eye on, and how data teams will evolve over the next 5-10 years.

If you're looking to build or expand upon a microservices architecture, then you need to seriously consider an API gateway. An API gateway is a critical piece of infrastructure that can help you build a scalable, secure, and efficient microservices architecture. They are an essential part of any API strategy. It acts as a single point of entry for all your API traffic, making it easier to manage and monitor your API traffic.

In today’s competitive environment, organizations need to quickly and easily make decisions based on real-time data. That’s why we’re announcing Datastream for BigQuery, now available in preview, featuring seamless replication from operational database sources such as AlloyDB for PostgreSQL, PostgreSQL, MySQL, and Oracle, directly into BigQuery, Google Cloud’s serverless data warehouse.

There are many pros and cons for both GraphQL and REST APIs, but one of the areas where GraphQL really shines is API composition. Taking data from multiple APIs and combining them to make something new is a key part of delivering a useful service.

Recovering revenue is an important part of running a successful venture in the modern API economy. With an API product it can be easy to undervalue your services and, ultimately, your business. This is why many API providers turn to billing customers for their usage, but which API monetization method is best for your product stack? Moesif enables you to make smart, informed decisions around your customers and maximize the monetization of your business model.

We previously wrote how the data mesh architecture rose as an answer to the problems of the monolithic centralized data model. To recap, in the centralized data models, ETL or ELT data pipelines collect data from various enterprise data sources and ingest it into a single central data lake or data warehouse. Data consumers and business intelligence tools access the data from the central storage to drive insights and inform decision-making.

As organizations invest ever more heavily in modernizing their data stacks, data teams—the people who actually deliver the value of data to the business—are finding it increasingly difficult to manage the performance, cost, and quality of these complex systems. Data teams today find themselves in much the same boat as software teams were 10+ years ago. Software teams have dug themselves out the hole with DevOps best practices and tools—chief among them full-stack observability.

What’s harder than finding the right data architecture? Finding the right dedicated partner. Adverity gets both with Snowflake. Learn how the two organizations are moving into new markets and supplying even more reliable marketing data to Adverity customers. When a fast-growing SaaS business looks to expand its client base, it normally encounters two major challenges: In many cases, an external data solution provider can only help solve the scalability challenge.