The telecommunications industry continues to develop hybrid data architectures to support data workload virtualization and cloud migration. However, while the promise of the cloud remains essential—not just for data workloads but also for network virtualisation and B2B offerings—the sheer volume and scale of data in the industry require careful management of the “journey to the cloud.”

In this post I will demonstrate how Kafka Connect is integrated in the Cloudera Data Platform (CDP), allowing users to manage and monitor their connectors in Streams Messaging Manager while also touching on security features such as role-based access control and sensitive information handling. If you are a developer moving data in or out of Kafka, an administrator, or a security expert this post is for you. But before I introduce the nitty-gritty first let’s start with the basics.

A key consideration when buying an embedded analytics solution is not only whether it supports embedding of charts and reports, but that it can integrate analytics in a way that is indistinguishable from the experience of your application. Learn what white-label BI is.

Like all of our customers, Cloudera depends on the Cloudera Data Platform (CDP) to manage our day-to-day analytics and operational insights. Many aspects of our business live within this modern data architecture, providing all Clouderans the ability to ask, and answer, important questions for the business. Clouderans continuously push for improvements in the system, with the goal of driving up confidence in the data.

Every financial professional understands that the numbers matter a great deal when it comes to reporting financial results. Accuracy, consistency, and timeliness are important. Those same professionals also know that there’s substantive meaning behind those numbers and that it’s important to tell the stories that lend additional depth and context to the raw financial statements.

In April this year, we announced that Qlik had successfully achieved Google Cloud Ready – BigQuery Designation for its Qlik Sense® cloud analytics solution and Qlik Data Integration®. We continue increasing customer confidence by combining multiple Qlik solutions alongside Google Cloud BigQuery to both help activate SAP data, and now mainframe data as well.

You’ve likely been hearing different versions of the same idea now for a while. Enterprises in every industry are investing in technology and strategies to drive more value from all their data across their entire organization.

Switching to a modern ERP software system affords many benefits, including increased efficiency, improved accuracy, and better control over your company’s finances. It is also an excellent opportunity to revisit many of the business processes that sit outside of your core ERP system. As you set out to improve your financial and operational procedures, you have an opportunity to rethink the way you perform tax planning, transfer pricing, budgeting, reporting, and analytics.

In many organizations, transfer pricing adjustments are like a lot of other last-minute activities. They seem to be ignored throughout most of the annual cycle. Then, they suddenly take on a great importance at year-end. That leaves the tax team scrambling to address an entire year’s worth of transactions. It also leads to interdepartmental friction in many cases. If transfer pricing is changed retroactively for the entire year, that can have far-reaching implications.

A recent VentureBeat article , “4 AI trends: It’s all about scale in 2022 (so far),” highlighted the importance of scalability. I recommend you read the entire piece, but to me the key takeaway – AI at scale isn’t magic, it’s data – is reminiscent of the 1992 presidential election, when political consultant James Carville succinctly summarized the key to winning – “it’s the economy”.