Enterprise data assets are what feed the predictive analytic process, and any tool must facilitate easy integration with all the different types data sources required to answer critical business questions. Robust predictive analytics needs to access analytical and relational databases, OLAP cubes, flat files, and enterprise applications.
Welcome to the first article in a weekly series called “Ask a Data Scientist.” Once a week until you’ll see reader submitted questions answered by a practicing data scientist. Think of this new insideBIGDATA feature as a valuable resource for you to get up to speed in this flourishing area of technology. If you have a big data question you’d like answered, please just enter a comment below, or send me an e-mail.
This article is the second in an editorial series that has the goal to provide direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively in today’s climate of working to increase the value of corporate data assets.
Today at Big Data Innovation Summit 2014, GridGain Systems (www.GridGain.com), a leading innovator of open source in-memory computing solutions, announced the launch of the GridGain In-Memory Data Fabric, a comprehensive software solution that accelerates business operations and time to insights by enabling high-performance transactions, real-time streaming and ultra-fast analytics in a single, highly scalable data access and processing layer.
There is a vast array of predictive analytics tools, but not all are created equal. Software differs widely in terms of capability and usability — not all solutions can address all types of advanced analytics needs. There are different classes of analytics users — some need to build statistical models, others just need to use them.
In this new Guide to Big Data for Finance the goal is to provide direction for enterprise thought leaders on ways of leveraging big data technologies in support of analytics proficiencies designed to work more independently and effectively in today’s climate of working to increase the value of corporate data assets.
This article is the third in an editorial series that will review how predictive analytics helps your organization predict with confidence what will happen next so that you can make smarter decisions and improve business outcomes.. It is important to adopt a predictive analytics solution that meets the specific needs of different users and skill sets from beginners, […]