Artificial intelligence and analytics

Artificial intelligence technologies such as machine learning underpin the advanced analytics tools many large companies rely on for a competitive edge. As AI becomes pervasive, a wider range of companies will have access to Artificial intelligence tools to aid business decisions. Get the best news and information on artificial intelligence and analytics including AI tools, tips and more.

January 22, 2021 22 Jan'21
Looker, Google planning plenty of analytics collaborations

While collaboration with its parent company is prominent in Looker's plans, so are investments in analytics capabilities including embedded BI and natural language processing.
January 15, 2021 15 Jan'21
Data storytelling a key part of Yellowfin analytics platform

Data storytelling remains a focal point for Yellowfin. Stories, the vendor's narrative generation tool, features heavily in both its latest platform update and roadmap for 2021.
January 14, 2021 14 Jan'21
Assent Compliance automates text analytics with AWS

With more than 20,000 documents to review each month, Assent Compliance, a supply chain data management vendor, turned to AWS to automate its text analysis operations.
December 18, 2020 18 Dec'20
Analytics startups to watch in the coming year

The startup BI vendors to watch in 2021 are those companies attempting to extend data analysis beyond data scientists and trained analysts to ordinary business users.

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AI, blockchain and IoT convergence improves daily applications

IT pros may find IoT, blockchain and AI difficult to conceptualize as individual technologies, but together, the three can generate data, improve analysis and establish trust. Continue Reading
NLP uses in BI and analytics speak softly but carry a big stick

Self-service analytics vendors are adding NLP features to their tools to make them even easier to use. Learn about notable NLP applications as well as some caveats. Continue Reading
data scientist

A data scientist is a professional responsible for collecting, analyzing and interpreting extremely large amounts of data. The data scientist role is an offshoot of several traditional technical roles, including mathematician, scientist, ... Continue Reading

Weigh the pros and cons of technologies, products and projects you are considering.

Data science vs. machine learning vs. AI: How they work together

Data science, machine learning and AI are central to analytics and other enterprise uses. Here's what each involves and how combining them benefits organizations. Continue Reading
8 top data science applications and use cases for businesses

Data scientists engage in various applications to analyze data and create technologies. These are eight common ones, with examples from different organizations and industries. Continue Reading
Augmented analytics lead analytics trends for 2021

Augmented analytics adoption was one of the top trends for 2020. Adoption still seems strong for 2021 as well as personalization the role of AI in analytics overall. Continue Reading

Learn to apply best practices and optimize your operations.

The data science process: 6 key steps on analytics applications

The data science process includes a set of steps that data scientists take to gather, prepare and analyze data and present the analytics results to business users. Continue Reading
8 types of bias in data analysis and how to avoid them

Analytics can exhibit biases that affect the bottom line or incite social outrage through discrimination. It's important to address those biases before problems arise. Continue Reading
How to build a machine learning model in 7 steps

Building a viable, reliable and agile machine learning model that streamlines operations and bolsters business planning takes patience, preparation and perseverance. Continue Reading

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

How to create a data set for machine learning with limited data

A shortage of data for machine learning training sets can halt a company's AI development in its tracks. Turning to external sources and hidden data can solve the problem. Continue Reading
The threats of AI must be taken seriously to prevent harm

The risks of AI use are growing as the technology becomes more pervasive. Rather than laugh off the threats, businesses should move to mitigate them before they become headaches. Continue Reading
Combination of blockchain and AI makes models more transparent

Blockchain technology could play an important role in helping enterprises develop more explainable AI applications, something that is frequently lacking today. Continue Reading