Big Data

Big Data news, analysis, research, how-to, opinion, and video.

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Review: automates machine learning

Driverless AI really is able to create and train good machine learning models without requiring machine learning expertise from users

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Dremio: Simpler and faster data analytics

Built on Apache Arrow and Apache Parquet, Dremio brings self-service to data analysts and SQL queries to NoSQL data sources

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Apache PredictionIO: Easier machine learning with Spark

An open source project now under Apache’s guidance uses a template system for easy training and deployment of Spark-powered machine learning models

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R tutorial: Learn to crunch big data with R

Get started using the open source R programming language to do statistical computing and graphics on large data sets

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Your analytics strategy is obsolete

While analytics is a giant market and filled with confusing marketing speak, there are big trends shaping the industry that will dictate where organizations invest

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ETL is dead

ETL is hard. And it's limiting. Unfortunately, there wasn't a better way because of the constraints of data technology. Until now

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AI and quantum computing: technology that's fueling innovation and solving future problems

Far from being all about who'll be first to prove its value, it seems to be more about solving real world problems for future generations in hopes of a better world

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The rise and predominance of Apache Spark

Recent surveys and forecasts of technology adoption have consistently suggested that Apache Spark is being embraced at a rate that outperforms other big data frameworks

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11 open source tools to make the most of machine learning

Tap the predictive power of machine learning with these diverse, easy-to-implement libraries and frameworks

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Bossie Awards 2017: The best machine learning tools

InfoWorld picks the best open source software for machine learning and deep learning

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Bossie Awards 2017: The best databases and analytics tools

InfoWorld picks the best open source software for large-scale search, SQL, NoSQL, and streaming analytics

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The 80/20 data science dilemma

Most data scientists spend only 20 percent of their time on actual data analysis and 80 percent of their time finding, cleaning, and reorganizing huge amounts of data, which is an inefficient data strategy

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Using big data to improve customer experience and financial results

For enterprises both large and small, it’s important to have a strategy in place to better serve customers using collected information

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Ensuring big data and fast data performance with in-memory computing

In-memory computing offers speed and scalability for digital transformation initiatives

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Machine learning skills for software engineers

You don’t need to be a data scientist to do machine learning, but you do need data skills. Start with these

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Review: Domo is good BI, not great BI

Domo delivers on data sources and visualizations, but is harder to use and overpriced compared to Tableau, Qlik Sense, and Microsoft Power BI

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ONNX makes machine learning models portable, shareable

Microsoft and Facebook's machine learning model format aims to let devs choose frameworks freely and share trained models without hassle

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What is big data? Everything you need to know

Analyzing lots of data is only part pf what makes big data different from previous data analytics. Learn what the other three aspects are

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