Generative AI seems like it's shaking things up for process automation, like other industries. But in reality, artificial intelligence is less of a shake-up and more of a natural complement to the capabilities that support a process automation initiative. Imagine a world where AI can turn a PDF into a digital interface, or sort all the emails in an inbox and generate responses for an employee to review.

Using APIs allows companies to harness the power of modern connectivity to help them expand their global reach, transfer data, and improve integration. Although APIs enable businesses to simplify processes and enhance usability, they can use some optimization strategies to improve performance. If you plan to use APIs or consider using an API provider, try using these tips to help make the processes optimized to get the most out of them.

Adopting a new business intelligence (BI) solution requires a thorough understanding of its feature-set and functionality in order to ensure analytics is integrated into your business as seamlessly as possible and that the value of your new tool is realized. Previously, we have covered how Yellowfin can be used with Power BI as a complementary solution.

Data is an essential part of most businesses in today’s digital age. It helps provide insight into various business processes, including recruiting, product strategy, and more. That’s where API comes into play. An API is designed to help improve overall business strategy for several focus areas, including marketing and customer services. This software is valuable in many instances, but it’s important to ask a few essential questions before beginning the process of building an API.

Bloomreach Engagement, an omnichannel marketing automation product, now integrates with BigQuery, providing hyper-personalized customer experiences.

Discover how you stack up against industry benchmarks for Google Analytics 4, Google Search Console, and Google My Business metrics.

Perhaps your C-suite is already a bit crowded. The typical hierarchy will include a CEO, COO, CFO, CTO, CMO, CIO, and a few more. Adding another position may not be terribly appealing, but there is one C-suite role every company should consider—chief data and analytics officer (CDO or CDAO).

By the end of this two-part series, we will dive into what data warehouse architecture is and how to implement one for your organization. Part one will look at architectural layers and common data warehouse components, while part two dives into multi-tiered data warehouse architecture.

The importance of a well-structured data lake architecture cannot be overstated. As businesses work with an ever-increasing influx of data, the need for a robust, scalable, and efficient data storage solution becomes crucial. Let’s explore Data Lake Architecture Design—a concept revolutionizing how enterprises store, access, analyze, and compute their data.

Want to finally get proper context for your Google Analytics 4 data? Then this report is just what you need.