Systems | Development | Analytics | API | Testing

Merging Data Literacy With Data Pipeline Success

In general, the concepts of data literacy and creating successful data pipelines seem totally disconnected. Data literacy involves insuring that data consumers have the knowledge and capabilities to understand and interact with data in a way that will provide them with the answers and value they need to do their jobs and benefit their organizations. While data pipelines require technical expertise to move, connect, and store data across the company's data ecosystem.

Happy New Year from Yellowfin: Our 2023 Commitments

Happy New Year from the Yellowfin team, and welcome to our 2023 wrap-up! Following a year full of product feature updates, company changes and new initiatives, this blog provides a helpful summary for all our customers and followers on our future 2023 product roadmap for the Yellowfin embedded analytics suite, and a look back at last year’s biggest news.

Have You Got What It Takes To Be A Kickass Data Engineer?

In the data landscape, the people are represented by two separate yet equally important groups. The data engineers who design the Lego blocks and the data scientists who build something extraordinary out of them. These are their stories. DUN DUN! And we’re back! Last time, we went over the toolkit needed to get your foot in the door as a data engineer. You’ve gotten over the first hurdle, but I hope you haven’t fallen prey to the Dunning-Kruger Effect.

From Data Warehouse to Lakehouse

This is a guest post for Integrate.io written by Bill Inmon, an American computer scientist recognized as the "father of the data warehouse." Inmon wrote the first book and first magazine column about data warehousing, held the first conference about this topic, and was the first person to teach data warehousing classes.

What is Moderated Usability Testing?

Successful usability testing takes time and expertise to plan and execute. Moderated usability testing involves a process of user research, participant recruitment, testing user flows, and analyzing data. The end results will uncover prioritized problem areas that, when addressed, will provide new ways to satisfy and retain your users. Different UX methods are dynamically used depending on the team’s goals, product, and audience.

4 Strategies for Manufacturing Cycle Time Reduction

In recent years, manufacturers faced major disruptions. Supply chain issues, unexpected product demand spikes, and delivery driver shortages led to longer lead times. While you can’t completely control external factors like these, you have far more control over your own internal manufacturing cycle times. This post will cover what cycle times are, the benefits of reducing them, and four strategies to help with cycle time reduction. .

How to Integrate BI and Data Visualization Tools with a Data Lake

For the past 30 years, the primary data source for business intelligence (BI) and data visualization tools has generally been either a data warehouse or a data mart. But as enterprises today struggle to cope with the growing complexity, scale, and speed of data, it’s becoming clear that the data tools of 30 years ago weren’t designed to handle the enterprise data management challenges of today - especially with the growing variety and amounts of data that enterprises are generating.

Embrace freelancer certification to improve software testing

With today’s accelerated development schedules, your team will likely rely on high-quality testers to help create great user experiences and improve software testing outcomes. Many companies have turned to on-demand freelance testers to ramp up in-house teams for better, more thorough QA coverage. Here’s the catch; this strategy only works if the testers you employ have the right skills for the job.

6 ways Tosca 16.0 speeds up your Oracle deployments

In a digital-first world, delivering business apps with high efficiency and top-notch quality is critical to your business success and customer satisfaction. Oracle is a major ERP application used by the world’s biggest companies to ensure business runs smoothly, but Oracle deployments are heavy, risky, and slow. How can organizations make them more efficient?