Big Data
Big Data news, analysis, research, how-to, opinion, and video.
AI: the challenge of data
While AI has been getting all the press, the elephant in the room is training data
In 2018, can cloud, big data, and AI stand more turmoil?
We'll see several trends emerge in 2018 whose key focus will be on making new technology easy and consumable
Julia vs. Python: Julia language rises for data science
Python has turned into a data science and machine learning mainstay, while Julia was built from the ground up to do the job
In the rush to big data, we forgot about search
In the cloud era, we need to look at search to be the glue that lets us find the data and analyze it together, no matter where it lives
White Paper
4 Reasons Remote Monitoring is Your Best Move to Better Service
Download this free e-book to discover how companies are realizing proven returns with IoT-enabled remote monitoring, which can be quickly implemented and monetized.
The clash of big data and the cloud
Making good strategic design decisions about the locations of your data and processing is key
No, you shouldn’t keep all that data forever
Most of your old data is useless trash. So throw it away, rather than spend all the time and money hoping AI will figure something out about it
How in-memory computing drives digital transformation with HTAP
Meet in-memory computing (IMC) and hybrid transactional/analytical processing (HTAP), tech’s newest power couple
Are you treating your data as an asset?
The best thing you can do is encourage a culture that is data-focused, one that realizes the importance of security and privacy, as well as understanding that data is crucial to your organization’s success
Deep Dive
Machine learning megaguide: Amazon, Microsoft, Databricks, Google, HPE, IBM
Download InfoWorld's massive roundup of Amazon, Microsoft, Databricks, Google, HPE, and IBM machine learning toolkits
![wireless network - industrial internet of things edge [IoT] - edge computing](https://images.idgesg.net/images/article/2017/09/wireless_network_iot_internet_of_things_edge_computing_data_analytics__industrial_management_thinkstock_824082860_3x2_1200x800-100736487-small.3x2.jpg)
Azure Databricks: Fast analytics in the cloud with Apache Spark
Microsoft’s partnership with Databricks adds new analytics tools to Azure’s data platform
Use the cloud to create open, connected data lakes for AI, not data swamps
There needs to be a material change in the way people think of solving complex data problems
Spark tutorial: Get started with Apache Spark
A step by step guide to loading a dataset, applying a schema, writing simple queries, and querying real-time data with Structured Streaming
A speedy recovery: the key to good outcomes as health care’s dependence on data deepens
Data is transforming health care, but it is also making life-saving treatments far more vulnerable to IT system failures
Deep Dive
Public cloud megaguide: Amazon, Microsoft, Google, IBM, and Joyent compared
The top five public clouds pile on the services and options, while adding unique twists
What is Apache Spark? The big data analytics platform explained
Fast, flexible, and developer-friendly, Apache Spark is the leading platform for large-scale SQL, batch processing, stream processing, and machine learning
Review: H2O.ai automates machine learning
Driverless AI really is able to create and train good machine learning models without requiring machine learning expertise from users
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
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
Deep Dive
Quick guide: 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
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
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
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
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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