New Year’s Resolutions for your Data Management Strategy

Equifax analysis indicates that approximately 91.5 million consumers in the US either have no credit file, or have insufficient information in the file to generate a traditional credit score. Your visibility into credit applicants determines whether you will offer more loans or miss profitable opportunities. By giving you incre

When your teams are building products for competitive markets and demanding customers, the right insights can make all the difference. Join us for our monthly Coffee Chat webinars to learn how you help your whole organization make better decisions, take faster action—and deliver the kind of experiences that drive revenue, loyalty, and lifetime value.

No industry relies more on data analytics for innovation than telecommunications. From increases in data volumes, the rise of 5G, and more and more connected devices, only the organizations that invest in a modern data infrastructure will be prepared to integrate, process, and analyze the mountains of new data. What are you doing today to get ready?

In this webinar we will discuss a more modern view of the data lake and consider best practices for planning and implementing a scalable enterprise data lake. The flaws in early data lakes were often rooted in the expectations of data consumers who put a premium on self-service data analytics. However, with no data governance mechanisms, data lakes quickly became more of a glorified “dumping ground,” “data swamp,” or “beta lake” for organizational data.In recent years, though, some innovations have allowed the data lake to evolve into an agile yet managed environment for accumulating shared data resources that can be optimally used for competitive advantage. Data lakes have evolved beyond the original on-premises concept based solely on Hadoop and now include pretty much any distributed computing platform (Hadoop, Spark, EMR, serverless, etc.) and any storage mechanism (HDFS, S3, ADLS), either on-premises or in the cloud.