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Discover industry benchmarks for bounce rate, average time on page, and more to optimize your website’s performance and outshine competitors.

The shift from single public cloud architectures to hybrid multi-cloud continues at enterprises around the globe, as organizations look for greater control, lower costs, and improved performance. I had the opportunity recently to speak with Vaughn Eisler, director of business development at Equinix, about this massive shift and some of the complex reasons behind them. Eisler sees several reasons for the movement.

Data practitioners should bring best practices from BI, especially automated data integration, to data science.

Business intelligence (BI) platforms analyze and present all your data in a visually friendly way on reports, graphs, charts, and dashboards, making it easier to view insights about your operations. But how do you get data into these platforms in the first place? The easiest way is by using BI ETL tools that extract data from its source, transform that data into the correct format, and load it into a central repository like a data warehouse — a process known as Extract, Transform, and Load (ETL).

Self-service analytics, also known as self-service business intelligence (BI), means different things to different people. For some, it might just mean an interactive report which lets them drill up and down a hierarchy or maybe switch to a different metric. For others, it might mean complete freedom to access anything in the company’s data warehouse in order to generate strategic insight.

As CEO of Qlik, I have never been more excited about the market, our strategic vision, and the value we bring customers all around the world. We have always been focused on looking forward and providing the most comprehensive and trusted solutions to our customers. Now, with Talend's cloud data integration and data quality solutions, we can offer even more.

Traditional ETL processes are time-consuming and complicated to create and manage, making it difficult for businesses and developers to empower their apps with real-time data analytics capabilities. This is where a headless ETL platform can help. As a new approach to data integration, headless ETL solutions maximize data agility through a single API.