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TDWI Upside - Where Data Means Business

IT and Enterprise Data Management


Data Digest: Analytics for Marketing, Big Data Science Tools, Data Quality for Analytics

Learn how to use analytics to improve your marketing, select the best big data science tools, and improve data quality for more accurate analytics.

Innovation in Machine Intelligence May Be Unstoppable

The Leading Edge Forum contends that we are fast approaching a point where machine (artificial) intelligence will develop rapidly and impact every industry because crucial factors have aligned.

Data Digest: Data-Driven Decisions, Data Breaches, Voice Data

Learn a simple strategy for any enterprise to implement data-driven decision making, five steps for preparing for a data breach before it happens, and the implications of recent improvements in voice recognition.

Data Digest: Exploring Security Methods for IoT, Monetizing IoT Data, Managing Data Lakes

Learn why “lean security” principles might help you secure your IoT devices, how IoT data can create opportunities for profit, and how a well-managed data lake creates a fertile ground for predictive analytics.

Considering a Cloud-based EDW: Questions You Must Ask

Enterprise data warehousing in the cloud represents a major change in thinking as well as in architecture. Addressing these critical questions can help you judge the practical value of cloud EDW for your enterprise.

Data Digest: Data Quality Challenges, Open Source Pros and Cons, Cloud Computing Definitions

Learn how to approach common data quality problems, what pros and cons you face selecting open source analytics solutions, and definitions of 20 common cloud computing terms.

Data Digest: Use Cognitive Computing with Big Data, Maintain Your Data Quality, Secure Your Big Data

Learn about trends in cognitive computing that help enterprises manage big data, why you may be struggling with data quality and what to do about it, and 5 best practices in big data security.

Smart Things, Dumb Data

Just because devices collect data doesn't mean we can use it. Why data from IoT devices needs to be standardized.

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