If your Artificial Intelligence (AI) project is bogged down with a wasteful, time-consuming and expensive data-preparation strategy, it could put your career at risk. Here is how you can anticipate and optimize your data-access needs to more effectively determine AI project outcomes, while avoiding potential technology pitfalls.

Artificial Intelligence is a broad topic that encompasses natural language processing, speech and facial recognition,

Evidence continues to build that today’s data challenges – and tomorrow’s – will not be solved with yesterday’s solutions – traditional relational databases.

Pure-play Hadoop vendors have long been viewed in the market as key next-generation providers for data analytics. But when I talk to customers, it seems all I hear about are the shortcomings of Hadoop. With promises of minimizing data silos with the concept of a Data Lake, Hadoop has failed in its ability to consider the operational

Data Lake is a term of art that has grown out of the “Big Data” and Hadoop hype cycles. The early rationale for the concept of Data Lakes was to deal with the diversity and volume of enterprise data in a way that was not possible with neither Data Warehouses nor Data Marts. Since it was first coined, the term has become ubiquitous in the industry. As a result, the term saturates the marketplace – pushing the assumption that every enterprise needs to have some kind of Data Lake

Research organization TDWI recently published an online survey and assessment guide to help organizations determine how ready they are to adopt and implement Hadoop.

In the past few years, the number of organizations using Hadoop—or contemplating using it—has grown astronomically. Each organization has common questions about whether they are really ready to implement Hadoop, and what the best practices are for being successful.

For these reasons, TDWI developed an Online Hadoop

I met with a friend of mine the other day who, when it comes technology subjects, I like to say – “she knows enough to be dangerous.” During our lunch she asked me about Hadoop and if I could explain it to her because in her mind it was like teenage sex – “everyone is talking about it but very few people are actually doing it.”

I couldn’t help but laugh at the analogy and on one level I think she is right.  I participate in a lot of meetups around Dallas/Fort Worth and many of these