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Top Data Science Tools That Will Empower Your Data Exploration Processes

datapine

Data science has become an extremely rewarding career choice for people interested in extracting, manipulating, and generating insights out of large volumes of data. To fully leverage the power of data science, scientists often need to obtain skills in databases, statistical programming tools, and data visualizations.

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Data science vs. machine learning: What’s the difference?

IBM Big Data Hub

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

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Assisted Predictive Analytics Benefits All Team Members!

Smarten

Investment in predictive analytics benefits everyone in the organization, including business users and team members, data scientists and the organization in general. Predictive analytics provides support for data-driven, fact-based decisions and enables insight, perspective and clarity for improved business agility and efficiency.

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The top 15 big data and data analytics certifications

CIO Business Intelligence

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126
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Sensors, signals and synergy: Enhancing Downer’s data exploration with IBM

IBM Big Data Hub

With over 200 trains and a multitude of sensors, Downer has accumulated a vast amount of data. Fine-tuning data insights with enhanced collaboration and expertise Downer continuously works to enhance operational efficiency, minimizing maintenance costs and impacts to transportation schedules.

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How Skullcandy Uses Predictive and Sentiment Analysis to Understand Customers

Sisense

Mark’s team is constantly adapting to and meeting the challenges of a rapidly evolving business using cloud technologies, real-time analytics, data warehousing, and virtualization. What if we could use this data to focus our resources and deliver better products? Using Sentiment Analytics to Inform New Product Design Decisions.

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10 everyday machine learning use cases

IBM Big Data Hub

Marketers use ML for lead generation, data analytics, online searches and search engine optimization (SEO). ML algorithms and data science are how recommendation engines at sites like Amazon, Netflix and StitchFix make recommendations based on a user’s taste, browsing and shopping cart history.