EGUIDE:
In this guide, we provide the 10 most important things you need to know about GDPR, and a jargon-buster explanation for some of the key terminology.
EGUIDE:
Applying technology like machine learning to transaction data could significantly increase the proportion of money laundering activity that is detected. It is projects like this that are driving demand for data science skills. In this e-guide, read about the power of data against money laundering, and how to get the skills to turn data into gold.
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.
WHITE PAPER:
This resource evaluates the adoption of enterprise-wide, production-ready big data tools using market data from Forrester Research and a custom study from CenturyLink Technology Solutions.
EGUIDE:
In this expert e-guide, explore the reasons many businesses are hesitant to put BI systems in the cloud, including security and compliance concerns, and why the time to start evaluating BI in the cloud is now. Read now to discover Wayne Eckerson's top six considerations before jumping into a cloud BI project.
VIDEO:
There's value in big data for every organization, no matter the size or industry. But not every business has been able to reap the benefits completely -- only about 1% of companies (usually the big players) have been able to extract real value. That is, until now.
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 examines the value of metadata in business intelligence, and introduces a metadata modeling tool for managing access to all existing data sources and ensuring data trustworthiness.
EZINE:
The hype around data mining may have receded, but it remains a critical discipline for the data scientist. This issue of CW Europe looks at what exactly data mining is, how and when it is used – and why it should not be mistaken for business analytics.
