Analytics

Custom code to connect with data APIs is quickly becoming a thing of the past.

Facebook recently announced that it will effectively discontinue Facebook Analytics on June 30, 2021. The announcement was not particularly informative and was limited to pointing out ways of retaining the tool’s users by means of diverting business to other features that Facebook already offers. However, the reasons behind this decision were not addressed by Facebook and it brings up the question of what this means for the industry.

Companies deploying big data analytics to gain competitive advantage can quickly sour their successes by lacking a big data governance strategy. Which turns their data assets into data liabilities. In this article, we dive into the field of information governance and information management and explore how to set up and automate a big data governance program for success. Big data governance is a set of processes and principles that ensure the high value of data throughout its lifecycle.

The faster you can extract, transform, and load data from MongoDB, the better it is for your business processes and business intelligence systems. The problem is, most ETL solutions struggle to manage MongoDB’s dynamic schemas, NoSQL support, and JSON data types. That’s not the case with Xplenty – which was optimized for easy, no-fuss MongoDB integrations with ease: no custom code, no delays, no confusion.

The success of data-driven initiatives for enterprise organizations depends largely on the quality of data available for analysis. This axiom can be summarized simply as garbage in, garbage out: low-quality data that is inaccurate, inconsistent, or incomplete often results in low-validity data analytics that can lead to poor business decision-making.

According to IDG, when customers consider updating to the latest release of a product, they expect new features, enhanced security, and better performance, but increasingly want a more streamlined upgrade process. With each new release of CDP Private Cloud, this is exactly what we strive to deliver. Along with a host of new features and capabilities, we are improving the upgrade process to be as painless as possible.

Understandably, however, the many automation, AI and machine learning technologies that come with modern analytics solutions can sometimes be hard to keep up with. One area we get asked a lot about is ABM, which we offer with Yellowfin Signals, and what exact advantages it brings to the table for everyday analysis and insight generation.