This session will include a moderated Q&A featuring questions from the live audience.
It seems like everyone wants to be part of a data-driven organization. There’s certainly no arguing the importance of data when coupled with the power of analytics. We’ve developed numerous techniques to collect data from a multitude of sources: applications, systems, and even third-party sources. Unfortunately, most organizations have approached these data tasks as one-off, custom activities. The problems with this approach include that it’s time consuming, often requires programmer-level skills, and can’t scale to support the growth in users and data sources.
The data manufacturing process—the effort involved in identifying, qualifying, gathering, and preparing data for analysis—should be repeatable and automated. We should also be able to apply advanced analytics techniques such as machine learning and artificial intelligence to simplify the construction and automation of the multiple tasks and combinations of events necessary to deliver data as a finished product.
The concepts of assembly lines and supply chains have been used across many industries to simplify the delivery of products. It’s time to apply these techniques to deliver data in an agile, repeatable, and scalable manner.
During this presentation, we will review the benefits of developing the data supply chain and discuss where automation and advanced analysis techniques can dramatically improve the delivery speed and data quality to support your data decision-making activities.
You will learn:
- Data delivery obstacles in an analytics environment
- The principals and benefits of a data supply chain
- How to position and utilize automation and advanced analytics techniques to improve data delivery