The Credit Union Executive’s Guide to Data and Analytics

As technology adoption increases exponentially, organizations are challenged by the proliferation of data that the technology generates. Increasingly, Shared Services Global In-house Centers (GICs) are leading their organizations’ efforts to tame data and derive key insights from it. Based on our recent Pinnacle Model research on data & analytics maturity in SSCs/GICs, this webinar will show executives how they can build capabilities in their SSCs GICs to turn this challenge into a strategic asset, generating value and enhancing service delivery

The most effective way to formally govern business processes is to apply governance to the process rather than redefine the entire process. This is one of the core tenets to Non-Invasive Data Governance and it assumes that your business processes are defined in the first place. In this month’s RWDG webinar, Bob Seiner will address how to apply formal Data Governance to existing processes and how to engage governance communities when defining new business processes. There is a distinct advantage to taking the Non-Invasive Approach to apply governance to business processes and Bob will detail this advantage during this month’s webinar.

Today’s data-driven companies have a choice to make – where do we store our data? As the move to the cloud continues to be a driving factor, the choice becomes either the data warehouse (Snowflake et al) or the data lake (AWS S3 et al). There are pro’s and con’s for each approach. While the data warehouse will give you strong data management with analytics, they don’t do well with semi-structured and unstructured data with tightly coupled storage and compute, not to mention expensive vendor lock-in. On the other hand, data lakes allow you to store all kinds of data and are extremely affordable, but they’re only meant for storage and by themselves provide no direct value to an organization.

Join ADA and the Digital Analytics Association as we discuss the trends, challenges and innovations that are shaping the future of enterprise data science.