WHITE PAPER:
The following white paper explores the through the eyes of pioneering analyst, Tom Davenport, on the importance of the data scientist when it comes to success with big data and advanced analytics. Learn how they how they help, how to onboard or create them, and much more.
WHITE PAPER:
This valuable report examines the critical role of data integration in driving big data success. Read on to learn about the current state of data integration, the key challenges of big data, and more.
WHITE PAPER:
Access the following white paper to uncover a discovery and analytics platform that can give you more insight from your big data than what can be found with multiple systems. Get a firsthand look at how an all-inclusive discovery system can deliver faster and more powerful insights, ultimately improving your functions and profitability.
WHITE PAPER:
This resource explores why the contact center has remained a highly untapped source of customer insight, explains how recent advances are giving organizations the power to analyze voice interactions, and counts down three essential success factors that you should consider.
EBOOK:
This guide offers expert advice to help you get started with offloading your EDW to Hadoop. Follow these 5 steps to overcome some of the biggest challenges & learn best practices for freeing up your EDW to do the work it was meant to do: provide the insights you need through high-performance analytics and fast user queries.
WEBCAST:
This brief on-demand video introduces an analytics platform designed for today's big data 2.0 world that delivers the key capabilities you need in order to leverage all of your available data.
WHITE PAPER:
This resource introduces a data management and analytics approach that gives you the power to harness customer information to improve experiences and meet constantly changing consumer expectations.
EGUIDE:
Surging big data is changing data modeling techniques and app development cycles. Read on to discover what you should expect from big data's near-future and best practices when it comes to transitioning big data applications into the production stage.
