Systems | Development | Analytics | API | Testing

Retail Media's Business Case for Data Clean Rooms Part 1: Your Data Assets and Permissions

It’s hard to have a conversation in adtech today without hearing the words, “retail media.” The retail media wave is in full force, piquing the interest of any company with a strong, first-party relationship with consumers. Companies are now understanding the value of their data and how that data can power a new, high-margin media business. The two-sided network that exists between retailers and their brands turns into a flywheel for growth.

What is OLAP (Online Analytical Processing)?

Online Analytical Processing (OLAP) is a computing technology through which users can extract and query data to analyze it from different points of view. These typically high-speed and complex queries are performed on massive data volumes stored in a data lake, data warehouse, or other large-scale repositories. Typical OLAP applications include business intelligence (BI) and forecasting and reporting.

The Sliding Doors for the Essentials

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?

Episode 9: From cloud migration to real-time analytics | Davey Resource Group

Clinton McFall from Davey Resource Group explores the challenges of cloud migrations and the lessons learned along the way. McFall and his team tackle complex data challenges including client data isolation across large data lakes, managing asynchronous data collection from field technicians and safely leveraging GenAI to explore GIS data in new ways. Listen to learn about how the country’s 8th largest employee-owned company is using data to manage difficult environmental projects.

Databricks Mastery: Speed, productivity, and efficiency for Lakehouse

80% of data teams are facing challenges related to availability of tooling. Why? Modern data engineering is difficult and testing data engineering solutions is generally an ad-hoc, manual process. The good news – data teams that use DataOps practices and tools will be 10 times more productive. With this in mind, Unravel is hosting a live event to demonstrate how enhanced visibility and data-driven observability help you streamline your workflow, accelerate your data pipelines on the Databricks Data Intelligence Platform.

Improve Product Stickiness and User Adoption with Embedded Analytics

You’ve heard of throwing ideas at a wall until something sticks–as a product manager, you may find you’re doing the same with application features. For application teams, creating sticky applications that customers can rely on and continue using for years to come is key to maximizing revenue. Elements like intuitive interfaces, personalized experiences, seamless integrations, and valuable core functionalities all contribute to this stickiness.

3 Ways to Monetize Your Application Data with Embedded Analytics

Data is one of the most valuable commodities an organization has. Every company stores and manages a substantial amount of information. But how do you gain revenue from it? Here, we discuss three ways you can monetize data with an embedded analytics investment.

How to Set Up a Fully Managed Alerting Pipeline Using Confluent Cloud Audit Logs

In large organizations, Confluent Cloud is often simultaneously accessed by many different users along with business-critical applications, potentially across different lines of business. With so many individual pieces working together, the risk of an individual outage, error, or incident affecting other services increases. An incident could be constituted by a user clicking a wrong button, an application’s misconfiguration, or just a bug—you name it.