open data science

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By: IBM     Published Date: Oct 21, 2016
Between the Internet of Things, customer experience and loyalty programs, social network monitoring, connected enterprise systems and other information sources, today's organizations have access to more data than they ever had before-and frankly, more than they may know what to do with. The challenge is to not just understand that data, but actualize it and use it to recognize real business value. This ebook will walk you through a sample scenario with Albert, a data scientist who wants to put text analytics to work by using the Word2vec algorithm and other data science tools.
Tags : ibm, analytics, aps, aps data, open data science, data science, word2vec, enterprise applications
     IBM
By: IBM     Published Date: Jan 18, 2017
It's all well enough for an organization to collect every slice of data it can reach, but having more data doesn't mean you'll automatically get better insights. First, you have to figure out what you want from your data you have to find its value.
Tags : ibm, aps data, data science, open data science, analytics, enterprise applications
     IBM
By: IBM     Published Date: Jan 18, 2017
In the domain of data science, solving problems and answering questions through data analysis is standard practice. Data scientists experiment continuously by constructing models to predict outcomes or discover underlying patterns, with the goal of gaining new insights. But data scientists can only go so far without support.
Tags : ibm, analytics, aps data, open data science, data science, data engineers, enterprise applications
     IBM
By: IBM     Published Date: Jan 18, 2017
Data matters more than ever to business success. But value does not come from data alone. Rather, it comes from the insights enabled by data. No matter what your role is, or where you are in your data journey, you are looking for ways to drive innovation.
Tags : ibm, analytics, aps data, open data science, data science, apache spark, enterprise applications
     IBM
By: IBM     Published Date: May 12, 2017
In today’s world, the data is flowing from all directions: social media, phones, weather, location and sensor equipped devices, and more. Competing in this digital age requires the ability to analyze all of this data, and use it to drive decisions that mitigate risk, increase customer satisfaction and grow revenue. Using a combination of proprietary software and open source technology can give your data scientists and statisticians the analytical power they need to find and act on insights quickly. IBM® SPSS® Statistics provides all of the data analysis tools you need, and integrates with thousands of R extensions for maximum power and flexibility. In this next Data Science Central Webinar event, we will show how SPSS Statistics can help you keep up with the influx of new data and make faster, better business decisions without coding.
Tags : ibm, spss, data analysis, statistics, risk mitigation
     IBM
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