At the Data Science Association our members often complain about the major data engineering problem of finding the right tools and programming models to build both robust data processing pipelines and efficient ETL processes for data transformation and integration.…
Added by Michael Walker on May 19, 2016 at 10:00pm — No Comments
Added by Michael Walker on April 9, 2016 at 9:00am — No Comments
A new 2016 survey entitled "Big Data Executive Survey 2016" concludes that data variety is the top data priority for most firms. Seasoned data science practitioners have long known that …Continue
Watch out folks - there is a new breed of health analytics firms sprouting like weeds - mining "big data" about you and making broad and bold predictions about your state of health to make workplace decisions.
Added by Michael Walker on February 18, 2016 at 12:34am — No Comments
Added by Michael Walker on December 17, 2015 at 6:07pm — No Comments
Google recently open sourced TensorFlow providing access to a powerful machine learning system. TensorFlow is a machine learning library with tools for data scientists to design intelligent systems (interface for expressing machine learning algorithms and…Continue
Does human intelligence have any connection to the type of music a person listens to? Can we define human intelligence? How do you measure human intelligence? Do SAT scores accurately measure human intelligence? Is there any evidence that SAT scores accurately predict educational or workplace performance?
I am skeptical 1) that we…
Last week we discussed the importance of data scientists prioritizing client confidentiality and the concern of exposing high-value information to…Continue
Added by Michael Walker on October 1, 2015 at 8:07pm — No Comments
The Data Science Association (DSA) and Google is interested in learning more about your experience with tools and training. Click on the link below to take a 10-minute survey for data scientists.…Continue
Added by Michael Walker on October 1, 2015 at 7:53pm — No Comments
Many organizations are reluctant to create data science teams (internally or externally) because of information confidentiality and privacy concerns. It is dangerous to open the kimono to competition - disclosing high-value information about inner workings of the firm may cause…Continue
Added by Michael Walker on September 24, 2015 at 3:00pm — No Comments
Added by Michael Walker on June 1, 2015 at 7:30am — No Comments
Recent research using deep convolutional neural networks and new system architectures have demonstrated the ability of smart machines to autonomously learn to classify image scenes and identify…Continue
United States President Barack Obama recently introduced DJ Patil as the new Chief Data Scientist of the United States Government. See video: Data Science: Where are We Going?…Continue
I often receive phone calls from organizations, aspiring data scientists and reporters about whether data science would be a good career choice for women. My response is absolutely yes, for the following reasons:
Women are great contrarian…Continue
There is often confusion between the definitions of "data veracity" and "data quality".
Data veracity is sometimes thought as uncertain or imprecise data, yet may be more precisely defined as false or inaccurate data. The data may be intentionally, negligently or mistakenly falsified. Data veracity may be distinguished from data quality,…Continue
We all know models are always an illusion of reality - yet may or may not be useful. Data scientists should build both simple and complex models with reasonable and testable assumptions that capture what is…Continue
Added by Michael Walker on December 5, 2014 at 6:31pm — No Comments
While large data sets may provide significant value in certain cases, data diversity and integrating smart data points will provide more consistent actionable insights and high value intelligence leading to better decision-making.
For example, consider NFL football data. Focusing on large football game data sets is usually not helpful and often misleading creating…
The current (November 2014) United States election reminds us that sophisticated data science techniques are employed on the public in attempt to influence opinion and persuade votes. The slick television advertising, debate prevarications, and policy position distortions and exaggerations have soured many citizens on the current state of modern democracy. Indeed, most feel we are not getting the straight scoop - the…Continue