Big Data
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Helping your workforce become data-literate
How to start building a data-literate organization without extensive training
How to bring BI and analytics to modern nested data structures
Nested data structures are a boon to modeling, storage, and query performance, but pose challenges to traditional BI tools. Here’s how to overcome them
The wonders of AI—or the shortcomings of search?
Thus far, the case for AI seems to mainly center on how it is taking search to the next level
Big data analytics: The cloud-fueled shift now under way
Public clouds are the future of enterprise big data analytics, and their use is creating the unified platform needed to fully gain its value
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
Adding speed and scalability to existing applications with in-memory data grids
Powering data-intensive and time-sensitive applications with in-memory data grids (IMDGs)
PyTorch tutorial: Get started with deep learning in Python
Learn how to create a simple neural network, and a more accurate convolutional neural network, with the PyTorch deep learning library
Think every business should become a software business? Think again
Rather than view themselves as software companies, organizations need to think of themselves as data companies
The marvels of an event-based schema
When working with various data types at the speed of big data, this method is ideal for integrating and aggregating assorted information for the holistic value it provides
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
Unlocking the power of today’s big data through governance
Contrary to what some believe, data governance isn’t about creating a veil of secrecy around data
7 essential technologies for a modern data architecture
These key technologies are “re-platforming” the enterprise to enable faster, easier, more flexible access to large volumes of precious data
Review: Neo4j supercharges graph analytics
When it comes to tracking relationships, Neo4j is faster, more flexible, and more scalable than relational databases
Cython tutorial: How to speed up Python
How to use Cython and its Python-to-C compiler to give your Python applications a rocket boost
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
Get started with TensorFlow
Begin harnessing the power of Google’s open source machine learning library with InfoWorld's hands-on tutorial
What if the LOB had digital democratization
4 recommendations to set your IoT analytics strategy on the best course
Data preparation is the key to big data success
Common barriers to big data adoption, and how to adapt and overcome those challenges
Shopping for data: what’s fit for your purpose?
The data catalog (or data marketplace) makes finding and accessing data easier, another step toward data democratization
Deep Dive
Build an IoT analytics solution with big data tools
The Internet of things seems futuristic, but real systems are delivering real analytics value today. Here’s some real-world IoT advice from the field
Technology of the Year 2018: The best hardware, software, and cloud services
InfoWorld’s 2018 Technology of the Year Award winners recognize the best tools and technologies for software development, cloud computing, data analytics, and machine learning
InfoWorld’s 2018 Technology of the Year Award winners
InfoWorld editors and reviewers pick the year’s best software development, cloud computing, data analytics, and machine learning tools
What is big data analytics? Everything you need to know
Analyzing lots of data is only part of what makes big data analytics different from previous data analytics. Learn what the other aspects are
Harmonizing big data with an enterprise knowledge graph
In addition to streamlining how users retrieve diverse data via automation capabilities, a knowledge graph standardizes those data according to relevant business terms and models
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