With all the investments made in analytics, it’s time to stop buying into partial solutions that overpromise and underdeliver. It’s time to invest in answers. Only Teradata leverages all of the data, all of the time, so that customers can analyze anything, deploy anywhere, and deliver analytics that matter most to them. And we do it at scale, on-premises, in the Cloud, or anywhere in between.
We call this Pervasive Data Intelligence. It’s the answer to the complexity, cost, and inadequacy of today’s analytics. And it’s the way Teradata transforms how businesses work and people live through the power of data throughout the world. Join us and help create the era of Pervasive Data Intelligence.
The Data Scientist gathers intelligence from the massive streams of data that clients gather each day. Due to the volume of data, its multi-structured nature, and the various advanced analysis involved, MapReduce and other advanced software available with, for example, Teradata and Hadoop are used to supplement or in place of traditional SQL analysis. Data can originate anywhere; from sales records, web logs, and web crawlers to jet engines, electronic switches, and other sources. The Data Scientist sifts through the data for useful nuggets of information, and then presents results to the client to allow business decisions to be made on the findings. The Data Scientist captures, sorts, and determines what is relevant in the data.
The analysis process involves assembling and preparing the data, writing the software programs, and executing the actual analysis. Advanced analysis is required on the data that includes data mining and statistical analysis. The Data Scientist will have a strong analytic background, typically in computer science or mathematics, and the application of statistics. Computer science programming expertise is desirable to analyze the data and provide intelligence that leads to better business decisions or new products. Techniques are used to detect patterns in large volumes of data for applications such as forecasting, response modeling, fraud detection, and segmentation. Industry specific methods and solutions are used to solve industry specific tasks. Strong communication skills are required to convey complex analytical results to business sponsors of programs. The Data Scientist provides solutions in the cloud, on premises, and in hybrid environments. The Data Scientist may be the Project Tech Lead on a project.