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BI Journal Volume 23 Number 2 Cover image

Business Intelligence Journal | Vol 23, No 2
TDWI Member Exclusive

January 22, 2019

Customers at big box stores are famous for flocking to sampling stations that offer tiny paper cups of food and drink. The retailers are hoping these samples are large enough for customers to be able to make a decision about whether they wish to buy the full-size product. In this issue of the Business Intelligence Journal, Hesham Saadawi and Azeddine Khir look at how sampling lets you use fewer resources and improve analytics response time so you can make faster, better decisions by analyzing only a portion of your big data.

Samples aren’t all a retailer can share with its customers, though. Hugh J. Watson and Brandon Obenauf look at how and why an enterprise might want to share its analytics tools with their customers or the public.

Speaking of making faster decisions, Gary Bordey looks at how the benefits of agility can be applied to your data governance design. Agility is also the focus of Dr. Kandathil K. Jacob, who explains how you can create an agile and insight-driven enterprise in just six steps with design thinking.

Our experts are focused on where you’re storing the data you use to make those decisions. Are you still analyzing data stuck in a data warehouse? As Scott Barnes, Tracy Ring Cryder, Stephen J. Smith, and Ed White discuss, perhaps it’s time to use new technology in the form of a data lake to get the most from your data. They look at the question of replacing a data warehouse with a data lake and how or if the two technologies can complement each other.

Taking the idea of new technologies and methodologies a step further, Puneet Pandit explains how applying AI and machine learning to healthcare can improve performance in that industry. When it comes to solving problems, our TDWI Best Practices Award winners have created some powerful and unique solutions to their problems. Read our summaries in this issue.

Our BI StatShots this issue looks especially at the problems that make data managers restless as they begin to modernize their analytics environments.

As always, we welcome your feedback at [email protected].

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