insightsoftware to Strengthen xP&A and Write-Back Capabilities in Qlik With Fiplana Acquisition
Deal will extend insightsoftware’s operational planning, reporting, and analytics capabilities in the Qlik ecosystem.
Defining Asynchronous Microservice APIs for Fraud Detection | Designing Event-Driven Microservices
In this video, Wade explores the process of decomposing a monolith into a series of microservices. You'll see how Tributary bank extracts a variety of API methods from an existing monolith. Tributary Bank wants to decompose its monolith into a series of microservices. They are going to start with their Fraud Detection service. However, before they can start, they first have to untangle the existing code. They will need to define a clean API that will allow them to move the functionality to an asynchronous, event-driven microservice.
Log and Event Analytics on Databricks: Overview and Use Cases
Built on the foundation of Apache Spark, Databricks is a unified, open data lakehouse platform that empowers customers to efficiently and cost-effectively process, store, manage, and analyze large volumes of enterprise data.
Unify your data: AI and Analytics in an Open Lakehouse
Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses. Nearly two years ago, Cloudera announced the general availability of Apache Iceberg in the Cloudera platform, which helps users avoid vendor lock-in and implement an open lakehouse. With an open data lakehouse powered by Apache Iceberg, businesses can better tap into the power of analytics and AI.
Bringing Financial Services Business Use Cases to Life: Leveraging Data Analytics, ML/AI, and Gen AI
The financial services industry is undergoing a significant transformation, driven by the need for data-driven insights, digital transformation, and compliance with evolving regulations. In this context, Cloudera and TAI Solutions have partnered to help financial services customers accelerate their data-driven transformation, improve customer centricity, ensure compliance with regulations, enhance risk management, and drive innovation.
A Complete Guide to Data Analytics
Data analytics is the science of analyzing raw data to draw conclusions about it. The process involves examining extensive data sets to uncover hidden patterns, correlations, and other insights. With today’s technology, data analytics can go beyond traditional analysis, incorporating artificial intelligence (AI) and machine learning (ML) algorithms that help process information faster than manual methods.
Implementing a data fabric: From silos to insights
Learn how a data fabric can add value by maximizing the value of a company’s data infrastructure.
How to solve the data discoverability problem with Data Portal and Flink
Learn how the Data Portal and Apache Flink in Confluent Cloud can help developers and data practitioners find the data they need to quickly create new data products.