Bring Your Business Analytics to Life with Automation

From AI and machine learning to data discovery and real-time analytics, a strong data architecture strategy is critical to supporting your organization's data-driven goals. Greater speed, flexibility, and scalability are common wish-list items, alongside smarter data governance and security capabilities. Many new technologies and approaches have come to the forefront of data architecture discussions, including data lakes, in-memory databases and engines like Spark and cloud services of all shapes and sizes.

Fanatics, a popular sports apparel website and fan gear merchandiser, needed to ingest terabytes of data from multiple historical and streaming sources transactional, e-commerce, and back-office systems to a data lake on Amazon S3. Once ingested, the data would be analyzed to better identify, predict, and fulfill customer needs related to the products Fanatics offers in over 300 online and offline stores. To accomplish this, Fanatics chose Attunity Replicate, a software solution featuring continuous data capture (CDC) and parallel threading for streaming data in real time from multiple sources into a data lake on Amazon S3. The data can then be consumed in Apache Kafka for real-time analytics. Attunity helps Fanatics avoid the heavy lifting of manually extracting data from disparate sources and enables the organization to see results in real time.

If you are looking for the scalability and performance needed to support interactive, ad hoc analytics on billions of rows – and with SQL – this latest Data Science Central webinar will show you how to combine distributed, columnar storage and parallel query processing with powerful aggregate functions to deliver faster time to insight using modern, on-demand analytics, as well as how to leverage the power of Kafka and Spark connectors to plug into existing data pipelines. We will discuss the architectural overview of columnar databases, share real-world use cases and give a live demonstration.

What does it mean to activate a Data Governance policy? Can an inactive policy be effective? Data Governance policies can address different things depending on the organization. Some policies are very general and introduce the awareness of formal Data Governance to the organization. Other policies address specific needs like Data Quality, data documentation, and data protection. Join Bob Seiner and a special guest for this RWDG webinar where they will tackle of the subject of how to develop and deploy an active Data Governance policy. Bob and his guest will provide specific examples of policy components and examples of how organizations use policies to govern their data.