As I have explored in this “Sliding Doors” blog series, identifying the right door to create value with data can prove quite challenging - and once that door is opened, the journey ahead can seem daunting. But what if there was a way to make that journey a bit easier? Maybe it’s time to get back to basics… Who needs to hear this?

For data engineers, the Generative AI (Gen AI) era is a transformative shift in how we approach data architecture and analytics. Professionals at the forefront of this shift will be gathering in San Francisco, at the Data+AI Summit June 10-13. Attendees will be exploring tools that integrate with Databricks Intelligent Data Platform that decrease data management costs and improve data's impact on business outcomes.

Making operational decisions in a tight timeframe is critical to the success of an organization. Real-time data ingestion enables quicker data availability, in turn enabling timely decision-making. Real-time ingestion is foundational to our digital transformation at Discover Financial Services. As a senior manager leading the streaming and real-time data platforms at Discover, I don’t want to be in the data replication business manually.

Earlier today, Qlik announced its expanded role as a Snowflake Cortex launch partner, and this article explains how the two solutions work together to benefit our customers. Let’s begin by quickly reviewing Snowflake Cortex.

Our ability to tell stories is an art form as old as language itself. From ancient cave paintings to oral traditions passed through generations, the essence of stories has evolved alongside our communication methods. It began with visual tales etched on cave walls, transitioned into spoken narratives, and eventually found its way into written, printed, and typed forms.

I have been having quite a bit of fun in this blog series exploring the “sliding doors” (or divergent paths) that organizations can take with their AI and data initiatives. The right door can lead to great value, as I covered in my previous posts on ESG reporting, data products, and responsible AI.

At Qlik, we're witnessing a thrilling shift in the landscape of data analysis, customer engagement, and decision-making processes, all thanks to the advent of generative AI, especially Large Language Models (LLMs). The potential for transformation across all sectors is enormous, but the journey toward integration can be daunting for many businesses with many leaders wondering where to start in integrating the exciting capabilities of AI into their daily workflows.

In this blog series, I have been exploring the “sliding doors” – or divergent paths - organizations can take with data and analytics. Sometimes, grabbing the wrong door means missing out on creating the most value with your data. But in some instances, it can also lead you on a more serious path of breach of compliance with regulations.

Data engineers play a crucial role in leveraging the immense potential of SAP data to drive smarter decisions and foster innovation. However, integrating and analyzing this valuable information can be complex and time-consuming. But it doesn’t need to be. In this blog post, we will explore how Qlik Cloud Data Integration and Databricks together make it much easier to harness the power of SAP data and blend that data in Databricks, in a cost-effective manner.

Perhaps it's the awe-inspiring films about space exploration (my personal favorite – Apollo 13) that evoke the image of NASA as a place buzzing with activity, filled with screens displaying data, charts, and ALWAYS a big countdown clock. However, one of NASA's most recent challenges may surprise you - the task of cracking open a billion-dollar canister filled with ancient asteroid dust.