Whitepapers
Datanami's white paper database contains reports from the leading thought-leaders and idea generators in the Datanami industry. 
The explosion in data, the vast array of new capabilities, and the dramatic increase in demands have changed how data needs to be moved, stored, processed and analyzed. But new architectures like data warehouses and lakes are creating additional bottlenecks within IT, because many existing processes are labor-intensive and insufficient. Read more…
Michael Stonebraker, A.M. Turing Award winner, believes real digital transformation must start with clean, accurate, consolidated data sets. His database management strategies are driving major changes at GE, Thomson Reuters, and Toyota. Read more…
For the financial sector, Know Your Customer (KYC) processes are a vital — and unavoidable — part of doing business today. With fraud, identity theft, and money laundering increasing and evolving all the time, you need watertight ways to predict risk. Read more…
Like other powerful technologies, AI and machine learning present significant opportunities. To reap the full benefits of ML, organizations must also mitigate the considerable risks it presents. This report outlines a set of actionable best practices for people, processes, and technology that can enable organizations to innovate with ML in a responsible manner. Read more…
The way we currently measure potential borrowers’ and other customers’ creditworthiness is broken. The credit scores that have become the gold standard are narrow, opaque, and easily manipulated measures that reward financial risk-taking and ignore responsible behaviors. Read more…
“Analyze-then-Store: The Journey to Continuous Intelligence” is a technical eBook intended for data architects and anyone else interested in learning how to design modern real-time data analytics and continuous intelligence solutions. Read more…
In this whitepaper, Eckerson Group discusses how to get maximum value from data lakes and how Qlik’s Data Integration Platform helps businesses get the most value out of their data lakes quickly, accurately, and with the agility to respond to shifting business needs. Read more…
Feature selection is a key step in building powerful and interpretable machine learning models, but it’s also one of the easiest to get wrong. The wrong features will give you inaccurate answers and may impact your ML models’ efficiency in ways you can’t predict. Read more…
Your machine learning models are only as good as the data you’re using to train and test them. So, how can you improve your datasets? This guide breaks down simple strategies to acquire better data and quick approaches and methods to fine-tune and manipulate your existing data will get you better testing results and insights. Read more…
If you’re developing or thinking of developing an AI strategy to transform your business, there’s a lot to consider, let us help. We’re the creator of the leading open source machine learning and artificial intelligence platform and our vision is to democratize AI for all and empower every company to be an AI company. Read more…
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