The phrase "analytics are able to" is correct and usable in written English.
It can be used when discussing the capabilities or functions of analytics in various contexts, such as data analysis or decision-making.
Example: "Analytics are able to identify trends and patterns that can inform business strategies."
Alternatives: "analytics can" or "analytics have the ability to".
Using images captured from airplanes, its machine learning analytics are able to tell how close risky vegetation is to a home.
As fraudsters change and improve their capabilities, institutions deploying data analytics are able to quickly defend themselves with an agile response to the emerging threats.
Complex analytics are able to discover data, run far more complex and advanced mathematical analysis than in previous decades and provide information visualizations that are informative and stunning.
In the business-to-business (B2B) world, platforms that provide predictive analytics are able to show sales and marketing teams exactly who to target for their next sale.
According to Google, the Analytics service allows website operators to "analyse visitor traffic and paint a complete picture of [the] audience and their needs". Essentially it means Google Analytics is able to create a record of what pages are visited and how a user has interacted with a given page.
And now I'd say to you, understanding data, being able to have either someone who has expertise in predictive analytics, being able to look out and forecast trends, those are areas that I think are just truly needed as we think about the future.
In e-commerce, Infinite Analytics was able to create a suite of products that allows for better personalization.
This is how Verto Analytics is able to determine when the personal assistants are being used, when, by who, and what user engagement is like.
More precisely, the data analytics is able to reduce the scope of the database because location of the shop and age of the buyer provide the information to help the system find out possible persons.
For example, this young person is at an elevated risk and the analytics were able to leverage an integrated practice model to help those youth.
In the end, only powerful analytics tools are able to extract "sense" from the exponentially growing amount of data and, as a consequence, data science becomes a strategic asset.
